Search results for: area flood likelihood model

Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

Procedia PDF Downloads 379

Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Franco Primo Soffietti, Diego Fernando Turello, Federico Pinto

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Shear waves that propagate through the ground impose deformations that must be taken into account in the design and assessment of buried longitudinal structures such as tunnels, pipelines, and piles. Conventional engineering approaches for seismic evaluation often rely on a Euler-Bernoulli beam models supported by a Winkler foundation. This approach, however, falls short in capturing the distortions induced when the structure is subjected to shear waves. To overcome these limitations, in the present work an analytical solution is proposed considering a Timoshenko beam and including transverse and rotational springs. The present research proposes ground springs derived as closed-form analytical solutions of the equations of elasticity including the seismic wavelength. These proposed springs extend the applicability of previous plane-strain models. By considering variations in displacements along the longitudinal direction, the presented approach ensures the springs do not approach zero at low frequencies. This characteristic makes them suitable for assessing pseudo-static cases, which typically govern structural forces in kinematic interaction analyses. The results obtained, validated against existing literature and a 3D Finite Element model, reveal several key insights: i) the cutoff frequency significantly influences transverse and rotational springs; ii) neglecting displacement variations along the structure axis (i.e., assuming plane-strain deformation) results in unrealistically low transverse springs, particularly for wavelengths shorter than the structure length; iii) disregarding lateral displacement components in rotational springs and neglecting variations along the structure axis leads to inaccurately low spring values, misrepresenting interaction phenomena; iv) transverse springs exhibit a notable drop in resonance frequency, followed by increasing damping as frequency rises; v) rotational springs show minor frequency-dependent variations, with radiation damping occurring beyond resonance frequencies, starting from negative values. This comprehensive analysis sheds light on the complex behavior of embedded longitudinal structures when subjected to shear waves and provides valuable insights for the seismic assessment.

Keywords: shear waves, Timoshenko beams, Winkler springs, sol-structure interaction

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Authors: Saveria Capecchi

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In this paper, the results of qualitative content research on postfeminist female representation in contemporary Western media (advertising, television series, films, social media) are presented. Female role models spectacularized in media culture are an important part of the development of social identities and could inspire new generations. Postfeminist cultural texts have given rise to heated debate between gender and media studies scholars. There are those who claim they are commercial products seeking to sell feminism to women, a feminism whose political and subversive role is completely distorted and linked to the commercial interests of the cosmetics, fashion, fitness and cosmetic surgery industries, in which women’s ‘power’ lies mainly in their power to seduce. There are those who consider them feminist manifestos because they represent independent ‘modern women’ free from male control who aspire to achieve professionally and overcome gender stereotypes like that of the ‘housewife-mother’. Major findings of the research show that feminist principles have been gradually absorbed by the cultural industry and adapted to its commercial needs, resulting in the dissemination of contradictory values. On the one hand, in line with feminist arguments, patriarchal ideology is condemned and the concepts of equality and equal opportunity between men and women are promoted. On the other hand, feminist principles and demands are ascribed to individualism, which translates into the slogan: women are free to decide for themselves, even to objectify their own bodies. In particular, it is observed that femvertising trend in media industry is changing female representation moving away from classic stereotypes: the feminine beauty ideal of slenderness, emphasized in the media since the seventies, is ultimately challenged by the ‘curvy’ body model, which is considered to be more inclusive and based on the concept of ‘natural beauty’. Another aspect of change is the ‘anti-romantic’ revolution performed by some heroines, who are not in search of Prince Charming, in television drama and in the film industry. In conclusion, although femvertising tends to simplify and trivialize the concepts characterizing fourth-wave feminism (‘intersectionality’ and ‘inclusion’), it is also a tendency that enables the challenging of media imagery largely based on male viewpoints, interests and desires.

Keywords: feminine beauty ideal, femvertising, gender and media, postfeminism

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Authors: Xu Feifei

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The prevalence of COVID-19 currently is the biggest challenge to improving people's quality of life. Its impact on the health-related quality of life (HRQoL) is highly uncertain and has not been summarized so far. The aim of the present systematic review was to assess and provide an up-to-date analysis of the impact of the COVID-19 pandemic on the HRQoL of participants who have been infected, have not been infected but isolated, frontline, with different diseases, and the general population. Therefore, an electronic search of the literature in PubMed databases was performed from 2019 to July 2022 (without date restriction). PRISMA guideline methodology was employed, and data regarding the HRQoL were extracted from eligible studies. Articles were included if they met the following inclusion criteria: (a) reports on the data collection of the health state utility values (HSUVs) related to COVID-19 from 2019 to 2021; (b) English language and peer-reviewed journals; and (c) original HSUV data; (d) using EQ-5D tool to quantify the HRQoL. To identify studies that reported the effects on COVID-19, data on the proportion of overall HSUVs of participants who had the outcome were collected and analyzed using a one-group meta-analysis. As a result, thirty-two studies fulfilled the inclusion criteria and, therefore, were included in the systematic review. A total of 45295 participants and provided 219 means of HSUVs during COVID-19 were included in this systematic review. The range of utility is from 0.224 to 1. The study included participants from Europe (n=16), North America (n=4), Asia (n=10), South America (n=1), and Africa (n=1). Twelve articles showed that the HRQoL of the participants who have been infected with COVID-19 (range of overall HSUVs from 0.6125 to 0.863). Two studies reported the population of frontline workers (the range of overall HSUVs from 0.82 to 0.93). Seven of the articles researched the participants who had not been infected with COVID-19 but suffered from morbidities during the pandemic (range of overall HSUVs from 0.5 to 0.96). Thirteen studies showed that the HRQoL of the respondents who have not been infected with COVID-19 and without any morbidities (range of overall HSUVs from 0.64 to 0.964). Moreover, eighteen articles reported the outcomes of overall HSUVs during the COVID-19 pandemic in different population groups. The estimate of overall HSUVs of direct COVID-19 experience population (n=1333) was 0.751 (95% CI 0.670 - 0.832, I2 = 98.64%); the estimate of frontline population (n=610) was 0.906 ((95% CI 0.854 – 0.957, I2 = 98.61%); participants with different disease (n=132) were 0.768 (95% CI 0.515 - 1.021, I2= 99.26%); general population without infection history (n=29,892) was 0.825 (95% CI 0.766 - 0.885, I2 =99.69%). Conclusively, taking into account these results, this systematic review might confirm that COVID-19 has a negative impact on the HRQoL of the infected population and illness population. It provides practical value for cost-effectiveness model analysis of health states related to COVID-19.

Keywords: COVID-19, health-related quality of life, meta-analysis, systematic review, utility value

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Piotr J. Skusiewicz, Johnathan Saul, Ijhar Rusli, Svetlana Aleksandrova, Stephen. F. Benjamin, Miroslaw Gall, Steve Pierson, Carol A. Roberts

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The application of turbocharging in automotive engines leads to swirling flow entering the catalyst. The behaviour of this type of flow within the catalyst has yet to be adequately documented. This work discusses the effect of swirling flow on the flow distribution in automotive exhaust catalysts. Compressed air supplied to a moving-block swirl generator allowed for swirling flow with variable intensities to be generated. Swirl intensities were measured at the swirl generator outlet using single-sensor hot-wire probes. The swirling flow was fed into diffusers with total angles of 10°, 30° and 180°. Downstream of the diffusers, a wash-coated diesel oxidation catalyst (DOC) of length 143.8 mm, diameter 76.2 mm and nominal cell density of 400 cpsi was fitted. Velocity profiles were measured at the outlet sleeve about 30 mm downstream of the monolith outlet using single-sensor hot-wire probes. Wall static pressure was recorded using a multi-tube manometer connected to pressure taps positioned along the diffuser walls. The results show that as swirl is increased, more of the flow is directed towards the diffuser walls. The velocity decreases around the centre-line and maximum velocities are observed close to the outer radius of the monolith for all flow rates. At the maximum swirl intensity, reversed flow was recorded near the centre of the monolith. Wall static pressure measurements in the 180° diffuser indicated no pressure recovery as the flow enters the diffuser. This is indicative of flow separation at the inlet to the diffuser. To gain insight into the flow structure, CFD simulations have been performed for the 180° diffuser for a flow rate of 63 g/s. The geometry of the model consists of the complete assembly from the upstream swirl generator to the outlet sleeve. Modelling of the flow in the monolith was achieved using the porous medium approach, where the monolith with parallel flow channels is modelled as a porous medium that resists the flow. A reasonably good agreement was achieved between the experimental and CFD results downstream of the monolith. The CFD simulations allowed visualisation of the separation zones and central toroidal recirculation zones that occur within the expansion region at certain swirl intensities which are highlighted.

Keywords: catalyst, computational fluid dynamics, diffuser, hot-wire anemometry, swirling flow

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Payling Harn

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LEGO® SERIOUS PLAY® is a kind of facilitated workshop of thinking and problem-solving approach. Participants built symbolic and metaphorical brick models in response to tasks given by the facilitator and presented these models to other participants. LEGO® SERIOUS PLAY® applied the positive psychological mechanism of Flow and positive emotions to help participants perceiving self-experience and unknown fact and increasing the happiness of life by building bricks and narrating story. At present, LEGO® SERIOUS PLAY® is often utilized for facilitating professional identity and strategy development to assist workers in career development. The researcher desires to apply LEGO® SERIOUS PLAY® to the career courses of college students in order to promote their career ability. This study aimed to use the facilitative method of LEGO® SERIOUS PLAY® to develop the career courses of college students, then explore the effects of Taiwanese college students' positive and negative emotions, career adaptabilities, and career sense of hope by LEGO® SERIOUS PLAY® career courses. The researcher regarded strength as the core concept and use the facilitative mode of LEGO® SERIOUS PLAY® to develop the 8 weeks’ career courses, which including ‘emotion of college life’ ‘career highlights’, ‘career strengths’, ‘professional identity’, ‘business model’, ‘career coping’, ‘strength guiding principles’, ‘career visions’,’ career hope’, etc. The researcher will adopt problem-oriented teaching method to give tasks which according to the weekly theme, use the facilitative mode of LEGO® SERIOUS PLAY® to guide participants to respond tasks by building bricks. Then participants will conduct group discussions, reports, and writing reflection journals weekly. Participants will be 24 second-grade college students. They will attend LEGO® SERIOUS PLAY® career courses for 2 hours a week. The researcher used’ ‘Career Adaptability Scale’ and ‘Career Hope Scale’ to conduct pre-test and post-test. The time points of implementation testing will be one week before courses starting, one day after courses ending respectively. Then the researcher will adopt repeated measures one-way ANOVA for analyzing data. The results revealed that the participants significantly presented immediate positive effect in career adaptability and career hope. The researcher hopes to construct the mode of LEGO® SERIOUS PLAY® career courses by this study and to make a substantial contribution to the future career teaching and researches of LEGO® SERIOUS PLAY®.

Keywords: LEGO® SERIOUS PLAY®, career courses, strength, positive and negative affect, career hope

Procedia PDF Downloads 247

Authors: Fagner O. Serrano, Danielle R. Bouchard, Todd A. Duhame

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Walking cadence (steps/min) is an effective way to prescribe exercise so an individual can reach a moderate intensity, which is recommended to optimize health benefits. To our knowledge, there is no study on the required walking cadence to reach a moderate intensity for people that present chronic conditions or risk factors for chronic conditions such as Cardiovascular Diseases (CVD). The objectives of this study were: 1- to identify the walking cadence needed for people at risk of CVD to a reach moderate intensity, and 2- to develop and test an equation using clinical variables to help professionals working with individuals at risk of CVD to estimate the walking cadence needed to reach moderate intensity. Ninety-one people presenting a minimum of two risk factors for CVD completed a medically supervised graded exercise test to assess maximum oxygen consumption at the first visit. The last visit consisted of recording walking cadence using a foot pod Garmin FR-60 and a Polar heart rate monitor, aiming to get participants to reach 40% of their maximal oxygen consumption using a portable metabolic cart on an indoor flat surface. The equation to predict the walking cadence needed to reach moderate intensity in this sample was developed as follows: The sample was randomly split in half and the equation was developed with one half of the participants, and validated using the other half. Body mass index, height, stride length, leg height, body weight, fitness level (VO2max), and self-selected cadence (over 200 meters) were measured using objective measured. Mean walking cadence to reach moderate intensity for people age 64.3 ± 10.3 years old at risk of CVD was 115.8  10.3 steps per minute. Body mass index, height, body weight, fitness level, and self-selected cadence were associated with walking cadence at moderate intensity when evaluated in bivariate analyses (r ranging from 0.22 to 0.52; all P values ≤0.05). Using linear regression analysis including all clinical variables associated in the bivariate analyses, body weight was the significant predictor of walking cadence for reaching a moderate intensity (ß=0.24; P=.018) explaining 13% of walking cadence to reach moderate intensity. The regression model created was Y = 134.4-0.24 X body weight (kg).Our findings suggest that people presenting two or more risk factors for CVD are reaching moderate intensity while walking at a cadence above the one officially recommended (116 steps per minute vs. 100 steps per minute) for healthy adults.

Keywords: cardiovascular disease, moderate intensity, older adults, walking cadence

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Authors: O. E. Akinyemi, P. O. Alege, O. O. Ajayi, L. A. Amaghionyediwe, A. A. Ogundipe

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Nigeria as an oil-producing developing country in Africa is one of the many countries that had been subsidizing consumption of fossil fuel. Despite the numerous advantage of this policy ranging from increased energy access, fostering economic and industrial development, protecting the poor households from oil price shocks, political considerations, among others; they have been found to impose economic cost, wasteful, inefficient, create price distortions discourage investment in the energy sector and contribute to environmental pollution. These negative consequences coupled with the fact that the policy had not been very successful at achieving some of its stated objectives, led to a number of organisations and countries such as the Group of 7 (G7), World Bank, International Monetary Fund (IMF), International Energy Agency (IEA), Organisation for Economic Co-operation and Development (OECD), among others call for global effort towards reforming fossil fuel subsidies. This call became necessary in view of seeking ways to harmonise certain existing policies which may by design hamper current effort at tackling environmental concerns such as climate change. This is in addition to driving a green growth strategy and low carbon development in achieving sustainable development. The energy sector is identified to play a vital role. This study thus investigates the prospects of using fuel subsidy reform as a viable tool in driving an economy that de-emphasizes carbon growth in Nigeria. The method used is the Johansen and Engle-Granger two-step Co-integration procedure in order to investigate the existence or otherwise of a long-run equilibrium relationship for the period 1971 to 2011. Its theoretical framework is rooted in the Environmental Kuznet Curve (EKC) hypothesis. In developing three case scenarios (case of subsidy payment, no subsidy payment and effective subsidy), findings from the study supported evidence of a long run sustainable equilibrium model. Also, estimation results reflected that the first and the second scenario do not significantly influence the indicator of environmental quality. The implication of this is that in reforming fuel subsidy to drive environmental quality for an economy like Nigeria, strong and effective regulatory framework (measure that was interacted with fuel subsidy to yield effective subsidy) is essential.

Keywords: environmental quality, fuel subsidy, green growth, low carbon growth strategy

Procedia PDF Downloads 317

Authors: Diana Islam, Juan Fang, Vito Fanelli, Bing Han, Julie Khang, Jianfeng Wu, Arthur S. Slutsky, Haibo Zhang

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Introduction: MSC delivery in preclinical models of ARDS has demonstrated significant improvements in lung function and recovery from acute injury. However, the role of MSC delivery in ARDS associated pulmonary fibrosis is not well understood. Some animal studies using bleomycin, asbestos, and silica-induced pulmonary fibrosis show that MSC delivery can suppress fibrosis. While other animal studies using radiation induced pulmonary fibrosis, liver, and kidney fibrosis models show that MSC delivery can contribute to fibrosis. Hypothesis: The beneficial and deleterious effects of MSC in ARDS are modulated by the lung microenvironment at the time of MSC delivery. Methods: To induce ARDS a two-hit mouse model of Hydrochloric acid (HCl) aspiration (day 0) and mechanical ventilation (MV) (day 2) was used. HCl and injurious MV generated fibrosis within 14-28 days. 0.5x106 mouse MSCs were delivered (via both intratracheal and intravenous routes) either in the active inflammatory phase (day 2) or during the remodeling phase (day 14) of ARDS (mouse fibroblasts or PBS used as a control). Lung injury accessed using inflammation score and elastance measurement. Pulmonary fibrosis was accessed using histological score, tissue collagen level, and collagen expression. In addition alveolar epithelial (E) and mesenchymal (M) marker expression profile was also measured. All measurements were taken at day 2, 14, and 28. Results: MSC delivery 2 days after HCl exacerbated lung injury and fibrosis compared to HCl alone, while the day 14 delivery showed protective effects. However in the absence of HCl, MSC significantly reduced the injurious MV-induced fibrosis. HCl injury suppressed E markers and up-regulated M markers. MSC delivery 2 days after HCl further amplified M marker expression, indicating their role in myofibroblast proliferation/activation. While with 14-day delivery E marker up-regulation was observed indicating their role in epithelial restoration. Conclusions: Early MSC delivery can be protective of injurious MV. Late MSC delivery during repair phase may also aid in recovery. However, early MSC delivery during the exudative inflammatory phase of HCl-induced ARDS can result in pro-fibrotic profiles. It is critical to understand the interaction between MSC and the lung microenvironment before MSC-based therapies are utilized for ARDS.

Keywords: acute respiratory distress syndrome (ARDS), mesenchymal stem cells (MSC), hydrochloric acid (HCl), mechanical ventilation (MV)

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Authors: Titir Bhattacharya, Tanika Chakraborty, Prabal K. De

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Maternal and child health continue to be a significant policy focus in developing countries, including India. An emerging model in health care is the creation of public and private partnerships. Since the construction of physical infrastructure is costly, governments at various levels have tried to implement social health insurance schemes where a trust calculates insurance premiums and medical payments. Typically, qualifying families get full subsidization of the premium and get access to private hospitals, in addition to low cost public hospitals, for their tertiary care needs. We analyze one such pioneering social insurance scheme in the Indian state of Andhra Pradesh (AP). The Rajiv Aarogyasri program (RA) was introduced by the Government of AP on a pilot basis in 2007 and implemented in 2008. In this paper, we first examine the extent to which access to reproductive health care changed. For example, the RA scheme reimburses hospital deliveries leading us to expect an increase in institutional deliveries, particularly in private hospitals. Second, we expect an increase in institutional deliveries to also improve child health outcomes. Hence, we estimate if the program improved infant and child mortality. We use District Level Health Survey data to create annual birth cohorts from 2000-2015. Since AP was the only state in which such a state insurance program was implemented, the neighboring states constituted a plausible control group. Combined with the policy timing, and the year of birth, we employ a difference-indifference strategy to identify the effects of RA on the residents of AP. We perform several checks against threats to identification, including testing for pre-treatment trends between the treatment and control states. We find that the policy significantly lowered infant and child mortality in AP. We also find that deliveries in private hospitals increased, and government hospitals decreased, showing a substitution effect of the relative price change. Finally, as expected, out-of-pocket costs declined for the treatment group. However, we do not find any significant effects for usual preventive care such as vaccination, showing that benefits of insurance schemes targeted at the tertiary level may not trickle down to the primary care level.

Keywords: public health insurance, maternal and child health, public-private choice

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Authors: Meng-Fei Cheng, Wei-Lun Chen, Han-Chang Ma, Chi-Che Tsai

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Recent K–12 Taiwan Science Education Curriculum Guideline emphasize the essential role of modeling curriculum in science learning; however, few modeling curricula have been designed and adopted in current science teaching. Therefore, this study aims to develop modeling curriculum on electric circuits to investigate any learning difficulties students have with modeling curriculum and further enhance modeling teaching. This study was conducted with 44 10th-grade students in Central Taiwan. Data collection included a students’ understanding of models in science (SUMS) survey that explored the students' epistemology of scientific models and modeling and a complex circuit problem to investigate the students’ modeling abilities. Data analysis included the following: (1) Paired sample t-tests were used to examine the improvement of students’ modeling abilities and conceptual understanding before and after the curriculum was taught. (2) Paired sample t-tests were also utilized to determine the students’ modeling abilities before and after the modeling activities, and a Pearson correlation was used to understand the relationship between students’ modeling abilities during the activities and on the posttest. (3) ANOVA analysis was used during different stages of the modeling curriculum to investigate the differences between the students’ who developed microscopic models and macroscopic models after the modeling curriculum was taught. (4) Independent sample t-tests were employed to determine whether the students who changed their models had significantly different understandings of scientific models than the students who did not change their models. The results revealed the following: (1) After the modeling curriculum was taught, the students had made significant progress in both their understanding of the science concept and their modeling abilities. In terms of science concepts, this modeling curriculum helped the students overcome the misconception that electric currents reduce after flowing through light bulbs. In terms of modeling abilities, this modeling curriculum helped students employ macroscopic or microscopic models to explain their observed phenomena. (2) Encouraging the students to explain scientific phenomena in different context prompts during the modeling process allowed them to convert their models to microscopic models, but it did not help them continuously employ microscopic models throughout the whole curriculum. The students finally consistently employed microscopic models when they had help visualizing the microscopic models. (3) During the modeling process, the students who revised their own models better understood that models can be changed than the students who did not revise their own models. Also, the students who revised their models to explain different scientific phenomena tended to regard models as explanatory tools. In short, this study explored different strategies to facilitate students’ modeling processes as well as their difficulties with the modeling process. The findings can be used to design and teach modeling curricula and help students enhance their modeling abilities.

Keywords: electric circuits, modeling curriculum, science learning, scientific model

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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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Authors: Adem Peker, Yüksel Eroğlu, İsmail Ay

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As the information and communication technologies have become embedded in everyday life of adolescents, both their possible benefits and risks to adolescents are being identified. The information and communication technologies provide opportunities for adolescents to connect with peers and to access to information. However, as with other social connections, users of information and communication devices have the potential to meet and interact with in harmful ways. One emerging example of such interaction is cyber bullying. Cyber bullying occurs when someone uses the information and communication technologies to harass or embarrass another person. Cyber bullying can take the form of malicious text messages and e-mails, spreading rumours, and excluding people from online groups. Cyber bullying has been linked to psychological problems for cyber bullies and victims. Therefore, it is important to determine how internet addiction contributes to cyber bullying. Building on this question, this study takes a closer look at the relationship between internet addiction and cyber bullying. For this purpose, in this study, based on descriptive relational model, it was hypothesized that loss of control, excessive desire to stay online, and negativity in social relationships, which are dimensions of internet addiction, would be associated positively with cyber bullying and victimization. Participants were 383 high school students (176 girls and 207 boys; mean age, 15.7 years). Internet addiction was measured by using Internet Addiction Scale. The Cyber Victim and Bullying Scale was utilized to measure cyber bullying and victimization. The scales were administered to the students in groups in the classrooms. In this study, stepwise regression analyses were utilized to examine the relationships between dimensions of internet addiction and cyber bullying and victimization. Before applying stepwise regression analysis, assumptions of regression were verified. According to stepwise regression analysis, cyber bullying was predicted by loss of control (β=.26, p<.001) and negativity in social relationships (β=.13, p<.001). These variables accounted for 9 % of the total variance, with the loss of control explaining the higher percentage (8 %). On the other hand, cyber victimization was predicted by loss of control (β=.19, p<.001) and negativity in social relationships (β=.12, p<.001). These variables altogether accounted for 8 % of the variance in cyber victimization, with the best predictor loss of control (7 % of the total variance). The results of this study demonstrated that, as expected, loss of control and negativity in social relationships predicted cyber bullying and victimization positively. However, excessive desire to stay online did not emerge a significant predictor of both cyberbullying and victimization. Consequently, this study would enhance our understanding of the predictors of cyber bullying and victimization since the results proposed that internet addiction is related with cyber bullying and victimization.

Keywords: cyber bullying, internet addiction, adolescents, regression

Procedia PDF Downloads 306

Authors: Chikang Wang, Jhongjheng Jian, Poming Huang

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Among a wide variety of pharmaceutical compounds, tetracycline antibiotics are one of the largest groups of pharmaceutical compounds extensively used in human and veterinary medicine to treat and prevent bacterial infections. Because it is water soluble, biologically active, stable and bio-refractory, release to the environment threatens aquatic life and increases the risk posed by antibiotic-resistant pathogens. In practice, due to its antibacterial nature, tetracycline cannot be effectively destructed by traditional biological methods. Hence, in this study, two advanced oxidation processes such as ozonation and sono-Fenton processes were conducted individually to degrade the tetracycline for investigating their feasibility on tetracycline degradation. Effect of operational variables on tetracycline degradation, release of nitrogen and change of toxicity were also proposed. Initial tetracycline concentration was 50 mg/L. To evaluate the efficiency of tetracycline degradation by ozonation, the ozone gas was produced by an ozone generator (Model LAB2B, Ozonia) and introduced into the reactor with different flows (25 - 500 mL/min) at varying pH levels (pH 3 - pH 11) and reaction temperatures (15 - 55°C). In sono-Fenton system, an ultrasonic transducer (Microson VCX 750, USA) operated at 20 kHz combined with H₂O₂ (2 mM) and Fe²⁺ (0.2 mM) were carried out at different pH levels (pH 3 - pH 11), aeration gas and flows (air and oxygen; 0.2 - 1.0 L/min), tetracycline concentrations (10 - 200 mg/L), reaction temperatures (15 - 55°C) and ultrasonic powers (25 - 200 Watts), respectively. Sole ultrasound was ineffective on tetracycline degradation, where the degradation efficiencies were lower than 10% with 60 min reaction. Contribution of Fe²⁺ and H₂O₂ on the degradation of tetracycline was significant, where the maximum tetracycline degradation efficiency in sono-Fenton process was as high as 91.3% followed by 45.8% mineralization. Effect of initial pH level on tetracycline degradation was insignificant from pH 3 to pH 6 but significantly decreased as the pH was greater than pH 7. Increase of the ultrasonic power was slightly increased the degradation efficiency of tetracycline, which indicated that the hydroxyl radicals dominated the oxidation of tetracycline. Effects of aeration of air or oxygen with different flows and reaction temperatures were insignificant. Ozonation showed better efficiencies in tetracycline degradation, where the optimum reaction condition was found at pH 3, 100 mL O₃/min and 25°C with 94% degradation and 60% mineralization. The toxicity of tetracycline was significantly decreased due to the mineralization of tetracycline. In addition, less than 10% of nitrogen content was released to solution phase as NH₃-N, and the most degraded tetracycline cannot be full mineralized to CO₂. The results shown in this study indicated that both the sono-Fenton process and ozonation can effectively degrade the tetracycline and reduce its toxicity at profitable condition. The costs of two systems needed to be further investigated to understand the feasibility in tetracycline degradation.

Keywords: degradation, detoxification, mineralization, ozonation, sono-Fenton process, tetracycline

Procedia PDF Downloads 264

Authors: A. Y. Tsidulko, T. M. Pankova, E. V. Grigorieva

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High-grade gliomas are the most frequent and most aggressive brain tumors which are characterized by active invasion of tumor cells into the surrounding brain tissue, where the extracellular matrix (ECM) plays a crucial role. Disruption of ECM can be involved in anticancer drugs effectiveness, side-effects and also in tumor relapses. The anti-inflammatory agent dexamethasone is a common drug used during high-grade glioma treatment for alleviating cerebral edema. Although dexamethasone is widely used in the clinic, its effects on normal brain tissue ECM remain poorly investigated. It is known that proteoglycans (PGs) are a major component of the extracellular matrix in the central nervous system. In our work, we studied the effects of dexamethasone on the ECM proteoglycans (syndecan-1, glypican-1, perlecan, versican, brevican, NG2, decorin, biglican, lumican) using RT-PCR in the experimental animal model. It was shown that proteoglycans in rat brain have age-specific expression patterns. In early post-natal rat brain (8 days old rat pups) overall PGs expression was quite high and mainly expressed PGs were biglycan, decorin, and syndecan-1. The overall transcriptional activity of PGs in adult rat brain is 1.5-fold decreased compared to post-natal brain. The expression pattern was changed as well with biglycan, decorin, syndecan-1, glypican-1 and brevican becoming almost equally expressed. PGs expression patterns create a specific tissue microenvironment that differs in developing and adult brain. Dexamethasone regimen close to the one used in the clinic during high-grade glioma treatment significantly affects proteoglycans expression. It was shown that overall PGs transcription activity is 1.5-2-folds increased after dexamethasone treatment. The most up-regulated PGs were biglycan, decorin, and lumican. The PGs expression pattern in adult brain changed after treatment becoming quite close to the expression pattern in developing brain. It is known that microenvironment in developing tissues promotes cells proliferation while in adult tissues proliferation is usually suppressed. The changes occurring in the adult brain after dexamethasone treatment may lead to re-activation of cell proliferation due to signals from changed microenvironment. Taken together obtained data show that dexamethasone treatment significantly affects the normal brain ECM, creating the appropriate microenvironment for tumor cells proliferation and thus can reduce the effectiveness of anticancer treatment and promote tumor relapses. This work has been supported by a Russian Science Foundation (RSF Grant 16-15-10243)

Keywords: dexamthasone, extracellular matrix, glioma, proteoglycan

Procedia PDF Downloads 192

Authors: Rafael Martins Manzano Silva, Jean-Francois Tremong

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Electrification of railway lines allows to increase speed, power, capacity and energetic efficiency of rolling stocks. However, this process of electrification is complex and costly. An electrification project is not just about design of catenary. It also includes installation of structures around electrification, as substation installation, electrical isolation, signalling, telecommunication and civil engineering structures. France has more than 30,000 km of railways, whose only 53% are electrified. The others 47% of railways use diesel locomotive and represent only 10% of the circulation (tons.km). For this reason, a new type of electrification, less expensive than the usual, is requested to enable the modernization of these railways. One solution could be the use of hybrids trains. This technology opens up new opportunities for less expensive infrastructure development such as the partial electrification of railway lines. In a partially electrified railway, the power supply of theses hybrid trains could be made either by the catenary or by the on-board energy storage system (ESS). Thus, the on-board ESS would feed the energetic needs of the train along the non-electrified zones while in electrified zones, the catenary would feed the train and recharge the on-board ESS. This paper’s objective deals with the technical and economic potential identification of partial electrification of railway lines. This study provides different scenarios of electrification by replacing the most expensive places to electrify using on-board ESS. The target is to reduce the cost of new electrification projects, i.e. reduce the cost of electrification infrastructures while not increasing the cost of rolling stocks. In this study, scenarios are constructed in function of the electrification’s cost of each structure. The electrification’s cost varies considerably because of the installation of catenary support in tunnels, bridges and viaducts is much more expensive than in others zones of the railway. These scenarios will be used to describe the power supply system and to choose between the catenary and the on-board energy storage depending on the position of the train on the railway. To identify the influence of each partial electrification scenario in the sizing of the on-board ESS, a model of the railway line and of the rolling stock is developed for a real case. This real case concerns a railway line located in the south of France. The energy consumption and the power demanded at each point of the line for each power supply (catenary or on-board ESS) are provided at the end of the simulation. Finally, the cost of a partial electrification is obtained by adding the civil engineering costs of the zones to be electrified plus the cost of the on-board ESS. The study of the technical and economic potential ends with the identification of the most economically interesting scenario of electrification.

Keywords: electrification, hybrid, railway, storage

Procedia PDF Downloads 421

Authors: Elhadi Nasr, Ibrahim Ramadan

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Biostratigraphical analyses of well sections from the Maragh Low in the Eastern Sirt Basin has allowed high resolution correlations to be undertaken. Full integration of this data with available palaeoenvironmental, lithological, gravity, seismic, aeromagnetic, igneous, radiometric and wireline log information and a geochemical analysis of source rock quality and distribution has led to a more detailed understanding of the geological and the structural history of this area. Pre Sirt Unconformity two superimposed rifting cycles have been identified. The oldest is represented by the Amal Group of sediments and is of Late Carboniferous, Kasimovian / Gzelian to Middle Triassic, Anisian age. Unconformably overlying is a younger rift cycle which is represented the Sarir Group of sediments and is of Early Cretaceous, late Neocomian to Aptian in age. Overlying the Sirt Unconformity is the marine Late Cretaceous section. An assessment of pyrolysis results and a palynofacies analysis has allowed hydrocarbon source facies and quality to be determined. There are a number of hydrocarbon source rock horizons in the Maragh Low, these are sometimes vertically stacked and they are of fair to excellent quality. The oldest identified source rock is the Triassic Shale, this unit is unconformably overlain by sandstones belonging to the Sarir Group and conformably overlies a Triassic Siltstone unit. Palynological dating of the Triassic Shale unit indicates a Middle Triassic, Anisian age. The Triassic Shale is interpreted to have been deposited in a lacustrine palaeoenvironment. This particularly is evidenced by the dark, fine grained, organic rich nature of the sediment and is supported by palynofacies analysis and by the recovery of fish fossils. Geochemical analysis of the Triassic Shale indicates total organic carbon varying between 1.37 and 3.53. S2 pyrolysate yields vary between 2.15 mg/g and 6.61 mg/g and hydrogen indices vary between 156.91 and 278.91. The source quality of the Triassic Shale varies from being of fair to very good / rich. Linked to thermal maturity it is now a very good source for light oil and gas. It was once a very good to rich oil source. The Early Barremian Shale was also deposited in a lacustrine palaeoenvironment. Recovered palynomorphs indicate an Early Cretaceous, late Neocomian to early Barremian age. The Early Barremian Shale is conformably underlain and overlain by sandstone units belonging to the Sarir Group of sediments which are also of Early Cretaceous age. Geochemical analysis of the Early Barremian Shale indicates that it is a good oil source and was originally very good. Total organic carbon varies between 3.59% and 7%. S2 varies between 6.30 mg/g and 10.39 mg/g and the hydrogen indices vary between 148.4 and 175.5. A Late Barremian Shale unit of this age has also been identified in the central Maragh Low. Geochemical analyses indicate that total organic carbon varies between 1.05 and 2.38%, S2 pyrolysate between 1.6 and 5.34 mg/g and the hydrogen index between 152.4 and 224.4. It is a good oil source rock which is now mature. In addition to the non marine hydrocarbon source rocks pre Sirt Unconformity, three formations in the overlying Late Cretaceous section also provide hydrocarbon quality source rocks. Interbedded shales within the Rachmat Formation of Late Cretaceous, early Campanian age have total organic carbon ranging between, 0.7 and 1.47%, S2 pyrolysate varying between 1.37 and 4.00 mg/g and hydrogen indices varying between 195.7 and 272.1. The indication is that this unit would provide a fair gas source to a good oil source. Geochemical analyses of the overlying Tagrifet Limestone indicate that total organic carbon varies between 0.26% and 1.01%. S2 pyrolysate varies between 1.21 and 2.16 mg/g and hydrogen indices vary between 195.7 and 465.4. For the overlying Sirt Shale Formation of Late Cretaceous, late Campanian age, total organic carbon varies between 1.04% and 1.51%, S2 pyrolysate varies between 4.65 mg/g and 6.99 mg/g and the hydrogen indices vary between 151 and 462.9. The study has proven that both the Sirt Shale Formation and the Tagrifet Limestone are good to very good and rich sources for oil in the Maragh Low. High resolution biostratigraphical interpretations have been integrated and calibrated with thermal maturity determinations (Vitrinite Reflectance (%Ro), Spore Colour Index (SCI) and Tmax (ºC) and the determined present day geothermal gradient of 25ºC / Km for the Maragh Low. Interpretation of generated basin modelling profiles allows a detailed prediction of timing of maturation development of these source horizons and leads to a determination of amounts of missing section at major unconformities. From the results the top of the oil window (0.72% Ro) is picked as high as 10,700’ and the base of the oil window (1.35% Ro) assuming a linear trend and by projection is picked as low as 18,000’ in the Maragh Low. For the Triassic Shale the early phase of oil generation was in the Late Palaeocene / Early to Middle Eocene and the main phase of oil generation was in the Middle to Late Eocene. The Early Barremian Shale reached the main phase of oil generation in the Early Oligocene with late generation being reached in the Middle Miocene. For the Rakb Group section (Rachmat Formation, Tagrifet Limestone and Sirt Shale Formation) the early phase of oil generation started in the Late Eocene with the main phase of generation being between the Early Oligocene and the Early Miocene. From studying maturity profiles and from regional considerations it can be predicted that up to 500’ of sediment may have been deposited and eroded by the Sirt Unconformity in the central Maragh Low while up to 2000’ of sediment may have been deposited and then eroded to the south of the trough.

Keywords: Geochemical analysis of the source rocks from wells in Eastern Sirt Basin.

Procedia PDF Downloads 402

Authors: Moustafa Osman Mohammed

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The photocurrent generations are influencing ultra-high efficiency solar cells based on self-assembled quantum dot (QD) nanostructures. Nanocrystal quantum dots (QD) provide a great enhancement toward solar cell efficiencies through the use of quantum confinement to tune absorbance across the solar spectrum enabled multi-exciton generation. Based on theoretical predictions, QDs have potential to improve systems efficiency in approximate regular electrons excitation intensity greater than 50%. In solar cell devices, an intermediate band formed by the electron levels in quantum dot systems. The spatial architecture is exploring how can solar cell integrate and produce not only high open circuit voltage (> 1.7 eV) but also large short-circuit currents due to the efficient absorption of sub-bandgap photons. In the proposed QD system, the structure allows barrier material to absorb wavelengths below 700 nm while multi-photon processes in the used quantum dots to absorb wavelengths up to 2 µm. The assembly of the electronic model is flexible to demonstrate the atoms and molecules structure and material properties to tune control energy bandgap of the barrier quantum dot to their respective optimum values. In terms of energy virtual conversion, the efficiency and cost of the electronic structure are unified outperform a pair of multi-junction solar cell that obtained in the rigorous test to quantify the errors. The milestone toward achieving the claimed high-efficiency solar cell device is controlling the edge causes of energy bandgap between the barrier material and quantum dot systems according to the media design limits. Despite this remarkable potential for high photocurrent generation, the achievable open-circuit voltage (Voc) is fundamentally limited due to non-radiative recombination processes in QD solar cells. The orientation of voltage recovery system is compared theoretically with experimental Voc variation in mediation upper–limit obtained one diode modeling form at the cells with different bandgap (Eg) as classified in the proposed spatial architecture. The opportunity for improvement Voc is valued approximately greater than 1V by using smaller QDs through QD solar cell recovery systems as confined to other micro and nano operations states.

Keywords: nanotechnology, photovoltaic solar cell, quantum systems, renewable energy, environmental modeling

Procedia PDF Downloads 148

Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

Procedia PDF Downloads 213

Authors: Rachel Cherner

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Introduction: The current study investigates several user characteristics that may predict the adoption of digital mental health supports. The extent to which individual characteristics predict preferences for functional elements of computer-mediated social support (CMSS) platforms and mental health (MH) apps is relatively unstudied. Aims: The present study seeks to illuminate the relationship between broad user characteristics and perceived attraction to CMSS platforms and MH apps. Methods: Participants (n=353) were recruited using convenience sampling methods (i.e., digital flyers, email distribution, and online survey forums). The sample was 68% male, and 32% female, with a mean age of 29. Participant racial and ethnic breakdown was 75% White, 7%, 5% Asian, and 5% Black or African American. Participants were asked to complete a 25-minute self-report questionnaire that included empirically validated measures assessing a battery of characteristics (i.e., subjective levels of anxiety/depression via PHQ-9 (Patient Health Questionnaire 9-item) and GAD-7 (Generalized Anxiety Disorder 7-item); attachment style via MAQ (Measure of Attachment Qualities); personality types via TIPI (The 10-Item Personality Inventory); growth mindset and mental health-seeking attitudes via GM (Growth Mindset Scale) and MHSAS (Mental Help Seeking Attitudes Scale)) and subsequent attitudes toward CMSS platforms and MH apps. Results: A stepwise linear regression was used to test if user characteristics significantly predicted attitudes towards key features of CMSS platforms and MH apps. The overall regression was statistically significant (R² =.20, F(1,344)=14.49, p<.000). Conclusion: This original study examines the clinical and sociocultural factors influencing decisions to use CMSS platforms and MH apps. Findings provide valuable insight for increasing adoption and engagement with digital mental health support. Fostering a growth mindset may be a method of increasing participant/patient engagement. In addition, CMSS platforms and MH apps may empower under-resourced and minority groups to gain basic access to mental health support. We do not assume this final model contains the best predictors of use; this is merely a preliminary step toward understanding the psychology and attitudes of CMSS platform/MH app users.

Keywords: computer-mediated social support platforms, digital mental health, growth mindset, health-seeking attitudes, mental health apps, user characteristics

Procedia PDF Downloads 86

Authors: Xiujing Chen, Thammananya Sakcharoen, Wilailuk Niyommaneerat

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China's tourism industry is in a state of shock and recovery, although COVID-19 has brought great impact and challenges to the tourism industry. The theory of sustainable development originates from the contradiction of increasing awareness of environmental protection and the pursuit of economic interests. The sustainable development of tourism should consider social, economic, and environmental factors and develop tourism in a planned and targeted way from the overall situation. Guilin is one of the popular tourist cities in China. However, there exist several problems in Guilin tourism, such as low quality of scenic spot construction and low efficiency of tourism resource development. Due to its unwell-managed, Guilin's tourism industry is facing problems such as supply and demand crowding pressure for tourists. According to the data from 2009 to 2019, there is a change in the degree of sustainable development of Guilin tourism. This research aimed to evaluate the sustainable development state of Guilin tourism using the DPSIR (driving force/pressure/state/impact/response) framework and to provide suggestions and recommendations for sustainable development in Guilin. An improved TOPSIS (technology for order preference by similarity to an ideal solution) model based on the entropy weights relationship is applied to the quantitative analysis and to analyze the mechanisms of sustainable development of tourism in Guilin. The DPSIR framework organizes indicators into sub-five categories: of which twenty-eight indicators related to sustainable aspects of Guilin tourism are classified. The study analyzed and summarized the economic, social, and ecological effects generated by tourism development in Guilin from 2009-2019. The results show that the conversion rate of tourism development in Guilin into regional economic benefits is more efficient than that into social benefits. Thus, tourism development is an important driving force of Guilin's economic growth. In addition, the study also analyzed the static weights of 28 relevant indicators of sustainable development of tourism in Guilin and ranked them from largest to smallest. Then it was found that the economic and social factors related to tourism revenue occupy the highest weight, which means that the economic and social development of Guilin can influence the sustainable development of Guilin tourism to a greater extent. Therefore, there is a two-way causal relationship between tourism development and economic growth in Guilin. At the same time, ecological development-related indicators also have relatively large weights, so ecological and environmental resources also have a great influence on the sustainable development of Guilin tourism.

Keywords: DPSIR framework, entropy weights analysis, sustainable development of tourism, TOPSIS analysis

Procedia PDF Downloads 89

Authors: Daniel Nigusse Tollosa, Erica James, Alexis Hurre, Meredith Tavener

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Introduction: Lifestyle behaviours such as healthy diet, regular physical activity and maintaining a healthy weight are essential for cancer survivors to improve the quality of life and longevity. However, there is no study that synthesis cancer survivor’s adherence to healthy lifestyle recommendations. The purpose of this review was to collate existing data on the prevalence of adherence to healthy behaviours and produce the pooled estimate among adult cancer survivors. Method: Multiple databases (Embase, Medline, Scopus, Web of Science and Google Scholar) were searched for relevant articles published since 2007, reporting cancer survivors adherence to more than two lifestyle behaviours based on the WCRF/AICR recommendations. The pooled prevalence of adherence to single and multiple behaviours (operationalized as adherence to more than 75% (3/4) of health behaviours included in a particular study) was calculated using a random effects model. Subgroup analysis adherence to multiple behaviours was undertaken corresponding to the mean survival years and year of publication. Results: A total of 3322 articles were generated through our search strategies. Of these, 51 studies matched our inclusion criteria, which presenting data from 2,620,586 adult cancer survivors. The highest prevalence of adherence was observed for smoking (pooled estimate: 87%, 95% CI: 85%, 88%) and alcohol intake (pooled estimate 83%, 95% CI: 81%, 86%), and the lowest was for fiber intake (pooled estimate: 31%, 95% CI: 21%, 40%). Thirteen studies were reported the proportion of cancer survivors (all used a simple summative index method) to multiple healthy behaviours, whereby the prevalence of adherence was ranged from 7% to 40% (pooled estimate 23%, 95% CI: 17% to 30%). Subgroup analysis suggest that short-term survivors ( < 5 years survival time) had relatively a better adherence to multiple behaviours (pooled estimate: 31%, 95% CI: 27%, 35%) than long-term ( > 5 years survival time) cancer survivors (pooled estimate: 25%, 95% CI: 14%, 36%). Pooling of estimates according to the year of publication (since 2007) also suggests an increasing trend of adherence to multiple behaviours over time. Conclusion: Overall, the adherence to multiple lifestyle behaviors was poor (not satisfactory), and relatively, it is a major concern for long-term than the short-term cancer survivor. Cancer survivors need to obey with healthy lifestyle recommendations related to physical activity, fruit and vegetable, fiber, red/processed meat and sodium intake.

Keywords: adherence, lifestyle behaviours, cancer survivors, WCRF/AICR

Procedia PDF Downloads 176

Authors: Oluwatosin M. A. Jesuyon

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In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

Procedia PDF Downloads 199

Authors: Anna M. Salejda, Urszula Tril, Grażyna Krasnowska

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The aim of this study was to analyze selected quality characteristics of cooked pork sausages manufactured with the addition of Sea buckthorn (Hippophae rhamnoides L.) berries preparations. Stuffings of model sausages consisted of pork, backfat, water and additives such a curing salt and sodium isoascorbate. Functional additives used in production process were two preparations obtained from dried Sea buckthorn berries in form of powder and brew. Powder of dried berries was added in amount of 1 and 3 g, while water infusion as a replacement of 50 and 100% ice water included in meat products formula. Control samples were produced without functional additives. Experimental stuffings were heat treated in water bath and stored for 4 weeks under cooled conditions (4±1ºC). Physical parameters of colour, texture profile and technological parameters as acidity, weight losses and water activity were estimated. The effect of Sea buckthorn berries preparations on lipid oxidation during storage of final products was determine by TBARS method. Studies have shown that addition of Sea buckthorn preparations to meat-fatty batters significant (P≤0.05) reduced the pH values of sausages samples after thermal treatment. Moreover, the addition of berries powder caused significant differences (P ≤ 0.05) in weight losses after cooking process. Analysis of results of texture profile analysis indicated, that utilization of infusion prepared from Sea buckthorn dried berries caused increase of springiness, gumminess and chewiness of final meat products. At the same time, the highest amount of Sea buckthorn berries powder in recipe caused the decrease of all measured texture parameters. Utilization of experimental preparations significantly decreased (P≤0.05) lightness (L* parameter of color) of meat products. Simultaneously, introduction of 1 and 3 grams of Sea buckthorn berries powder to meat-fatty batter increased redness (a* parameter) of samples under investigation. Higher content of substances reacting with thiobarbituric acid was observed in meat products produced without functional additives. It was observed that powder of Sea buckthorn berries added to meat-fatty batters caused higher protection against lipid oxidation in cooked sausages.

Keywords: sea buckthorn, meat products, texture, color parameters, lipid oxidation

Procedia PDF Downloads 292

Authors: Scott Cavinder

Abstract:

Surgical site infections (SSI) are a known complication to any surgical procedure and are one of the most common nosocomial infections. Globally it is estimated 300 million surgical procedures take place annually, with an incidence of SSI’s estimated to be 11 of 100 surgical patients developing an infection within 30 days after surgery. The specific purpose of the project is to address the PICOT (Problem, Intervention, Comparison, Outcome, Time) question: In patients who have undergone cardiothoracic or vascular surgery (P), does implementation of a post-operative care bundle based on current EBP (I) as compared to current clinical agency practice standards (C) result in a decrease of SSI (O) over a 12-week period (T)? Synthesis of Supporting Evidence: A literature search of five databases, including citation chasing, was performed, which yielded fourteen pieces of evidence ranging from high to good quality. Four common themes were identified for the prevention of SSI’s including use and removal of surgical dressings; use of topical antibiotics and antiseptics; implementation of evidence-based care bundles, and implementation of surveillance through auditing and feedback. The Iowa Model was selected as the framework to help guide this project as it is a multiphase change process which encourages clinicians to recognize opportunities for improvement in healthcare practice. Practice/Implementation: The process for this project will include recruiting postsurgical participants who have undergone cardiovascular or thoracic surgery prior to discharge at a Northwest Indiana Hospital. The patients will receive education, verbal instruction, and return demonstration. The patients will be followed for 12 weeks, and wounds assessed utilizing the National Healthcare Safety Network//Centers for Disease Control (NHSN/CDC) assessment tool and compared to the SSI rate of 2021. Key stakeholders will include two cardiovascular surgeons, four physician assistants, two advance practice nurses, medical assistant and patients. Method of Evaluation: Chi Square analysis will be utilized to establish statistical significance and similarities between the two groups. Main Results/Outcomes: The proposed outcome is the prevention of SSIs in the post-op cardiothoracic and vascular patient. Implication/Recommendation(s): Implementation of standardized post operative care bundles in the prevention of SSI in cardiovascular and thoracic surgical patients.

Keywords: cardiovascular, evidence based practice, infection, post-operative, prevention, thoracic, surgery

Procedia PDF Downloads 76

Authors: A. Rezaei, M. Huisman, W. Van Paepegem

Abstract:

Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

Procedia PDF Downloads 145

Authors: M. El-haj, Z. Olama, H. Holail

Abstract:

Single cell oils (SCOs) accumulated by oleaginous fungi have emerged as a potential alternative feedstock for biodiesel production. Five fungal strains were isolated from the Lebanese environment namely Fusarium oxysporum, Mucor hiemalis, Penicillium citrinum, Aspergillus tamari, and Aspergillus niger that have been selected among 39 oleaginous strains for their potential ability to accumulate lipids (lipid content was more than 40% on dry weight basis). Wide variations were recorded in the environmental factors that lead to maximum lipid production by fungi under test and were cultivated under submerged fermentation on medium containing glucose as a carbon source. The maximum lipid production was attained within 6-8 days, at pH range 6-7, 24 to 48 hours age of seed culture, 4 to 6.107 spores/ml inoculum level and 100 ml culture volume. Eleven culture conditions were examined for their significance on lipid production using Plackett-Burman factorial design. Reducing sugars and nitrogen source were the most significant factors affecting lipid production process. Maximum lipid yield was noticed with 15.62, 14.48, 12.75, 13.68 and 20.41g/l for Fusarium oxysporum, Mucor hiemalis, Penicillium citrinum, Aspergillus tamari, and Aspergillus niger respectively. A verification experiment was carried out to examine model validation and revealed more than 94% validity. The profile of extracted lipids from each fungal isolate was studied using thin layer chromatography (TLC) indicating the presence of monoacylglycerols, diaacylglycerols, free fatty acids, triacylglycerols and sterol esters. The fatty acids profiles were also determined by gas-chromatography coupled with flame ionization detector (GC-FID). Data revealed the presence of significant amount of oleic acid (29-36%), palmitic acid (18-24%), linoleic acid (26.8-35%), and low amount of other fatty acids in the extracted fungal oils which indicate that the fatty acid profiles were quite similar to that of conventional vegetable oil. The cost of lipid production could be further reduced with acid-pretreated lignocellulotic corncob waste, whey and date molasses to be utilized as the raw material for the oleaginous fungi. The results showed that the microbial lipid from the studied fungi was a potential alternative resource for biodiesel production.

Keywords: agro-industrial waste products, biodiesel, fatty acid, single cell oil, Lebanese environment, oleaginous fungi

Procedia PDF Downloads 401