Search results for: generalized propensity score

Authors: A. J. Al-Graitti, G. A. Khalid, P. Berthelson, A. Mason-Jones, R. Prabhu, M. D. Jones

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Motor vehicle related pedestrian road traffic collisions are a major road safety challenge, since they are a leading cause of death and serious injury worldwide, contributing to a third of the global disease burden. The auto rickshaw, which is a common form of urban transport in many developing countries, plays a major transport role, both as a vehicle for hire and for private use. The most common auto rickshaws are quite unlike ‘typical’ four-wheel motor vehicle, being typically characterised by three wheels, a non-tilting sheet-metal body or open frame construction, a canvas roof and side curtains, a small drivers’ cabin, handlebar controls and a passenger space at the rear. Given the propensity, in developing countries, for auto rickshaws to be used in mixed cityscapes, where pedestrians and vehicles share the roadway, the potential for auto rickshaw impacts with pedestrians is relatively high. Whilst auto rickshaws are used in some Western countries, their limited number and spatial separation from pedestrian walkways, as a result of city planning, has not resulted in significant accident statistics. Thus, auto rickshaws have not been subject to the vehicle impact related pedestrian crash kinematic analyses and/or injury mechanics assessment, typically associated with motor vehicle development in Western Europe, North America and Japan. This study presents a parametric analysis of auto rickshaw related pedestrian impacts by computational simulation, using a Finite Element model of an auto rickshaw and an LS-DYNA 50^th percentile male Hybrid III Anthropometric Test Device (dummy). Parametric variables include auto rickshaw impact velocity, auto rickshaw impact region (front, centre or offset) and relative pedestrian impact position (front, side and rear). The output data of each impact simulation was correlated against reported injury metrics, Head Injury Criterion (front, side and rear), Neck injury Criterion (front, side and rear), Abbreviated Injury Scale and reported risk level and adds greater understanding to the issue of auto rickshaw related pedestrian injury risk. The parametric analyses suggest that pedestrians are subject to a relatively high risk of injury during impacts with an auto rickshaw at velocities of 20 km/h or greater, which during some of the impact simulations may even risk fatalities. The present study provides valuable evidence for informing a series of recommendations and guidelines for making the auto rickshaw safer during collisions with pedestrians. Whilst it is acknowledged that the present research findings are based in the field of safety engineering and may over represent injury risk, compared to “Real World” accidents, many of the simulated interactions produced injury response values significantly greater than current threshold curves and thus, justify their inclusion in the study. To reduce the injury risk level and increase the safety of the auto rickshaw, there should be a reduction in the velocity of the auto rickshaw and, or, consideration of engineering solutions, such as retro fitting injury mitigation technologies to those auto rickshaw contact regions which are the subject of the greatest risk of producing pedestrian injury.

Keywords: auto rickshaw, finite element analysis, injury risk level, LS-DYNA, pedestrian impact

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Authors: Mahvish Anjum

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India is a land of craftsmen and a hub of many popular embroidery clusters. Chikankari is the name given to the delicate art of hand embroidery, traditionally practiced in the city of Lucknow and its environs. Chikankari not only provide employment to 250,000 artisans of different crafts but people from non-craft base also earn their livelihood by associating themselves with this craft. People working in this sector are exploited in term of working hours, low and irregular income, unsatisfactory work conditions, no legal protection and exposed to occupational health hazards. The present paper is an attempt to analyse occupational profile of workers engaged in Chikan embroidery industry. Being an empirical study, the entire work is based upon primary sources of data which have collected through field survey. Purposive random sampling has used for selection of data. Total 150 workers have surveyed through questionnaire technique in Lucknow city during October-November, 2017. For analysis of data Z-score, ANOVA, and Pearson correlation techniques are used. The result of present study indicates that artisans are exploited by the middle man and face the problem of late payment and long working hours because they are not directly associated with the manufacturers. Work conditions of the workers are quite poor such as improper ventilation, poor light and unhygienic conditions that adversely affect the health of workers.

Keywords: artisans, socio-economic status, unorganized industry, work condition

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Authors: Bhaskar Chakravorti, Christopher Tunnard, Ravi Shankar Chaturvedi

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This report introduces the Digital Evolution Index (DEI) as a way to gauge the transformation of economies in the advanced and developing world from traditional brick-and-mortar to digitally enabled. The DEI measures the digital trajectories of 50 countries to provide actionable, data-informed insights for businesses, investors and policymakers. Created by The Fletcher School, in collaboration with MasterCard Worldwide and DataCash, the DEI analyzes the key underlying drivers and barriers that govern a country’s evolution into a digital economy: Demand, Supply, Institutional Environment and Innovation. A longitudinal analysis of these four drivers during the years 2008 to 2013 reveals both the current state of a country’s digital economy, as well as changes over time. Combining these two measures allows us to assign each country to one of four Trajectory Zones: • Stand Out countries have shown high levels of digital development in the past and continue to remain on an upward trajectory. • Stall Out countries have achieved a high level of evolution in the past but are losing momentum and risk falling behind. • Break Out countries have the potential to develop strong digital economies. Though their overall score is still low, they are moving upward and are poised to become Stand Out countries in the future. • Watch Out countries face significant opportunities and challenges, with low scores on both current level and upward motion of their DEI. Some may be able to overcome limitations with clever innovations and stopgap measures, while others seem to be stuck.

Keywords: e-commerce, digital evolution, digital commerce ecosystems, e-consumer

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Ebtsam Aly Abou Hashish, Sharifah Abdulmuttalib Alsayed, Hend Abdu Alnajjar

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Background: Academic nurse educators play a crucial role in the educational environment, but the demands of their profession can lead to workaholism, which could result in an imbalance between work and personal life. Purpose: The study aimed to explore workaholism and life balance among academic nursing educators, as well as investigate the factors associated with workaholism. Methods: A mixed-methods design based on the ‘concurrent triangulation’ approach was employed. A convenience sample of 76 nurse educators completed the Dutch Work Addiction Scale (DUWAS) and the Life Balance Inventory (LBI), while a purposive sample of 20 nurse educators participated in semi-structured interviews. Inferential statistics and thematic analysis were used to analyze the data. Results: The researchers found a notable prevalence of workaholism among nurse educators, with 59.0 % reporting a mean score above 2.5 and 86.8 % perceiving an unbalanced life. Regression analysis indicated that workaholism negatively predicted life balance (B = 􀀀 0.404, p < 0.001). The qualitative findings derived three themes as determinants of workaholism: antecedents, consequences, and personal and institutional strategies to mitigate workaholism among nursing educators. Conclusion: Educational institutions should develop comprehensive approaches to support and develop their academicians, fostering a positive work environment, work-life balance, employee well-being, and professional development.

Keywords: workaholism, life balance, academic nurse educators, mixed-method

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Authors: Diana Ruth Caga-Anan

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Classroom management is a critical skill but the styles are constantly evolving. It is constantly under pressure particularly in the college education level due to diversity in student profiles, modes of delivery, and marketization of higher education. This study sought to analyze the extent of implementation of classroom management practices (CMPs) of the college instructors of the Hotel, Restaurant, and Institution Management of a premier university in the Philippines. It was also determined if their length of teaching affects their classroom management style. A questionnaire with sixteen 'evidenced-based' CMPs grouped into five critical features of classroom management, adopted from the literature search of Simonsen et al. (2008), was administered to 4 instructor-respondents and to their 88 students. Weighted mean scores of each of the CMPs revealed that there were differences between the instructors’ self-scores and their students’ ratings on their implementation of CMPs. The critical feature of classroom management 'actively engage students in observable ways' got the highest mean score, corresponding to 'always' from the instructors’ self-rating and 'frequently' from their students’ ratings. However, 'use a continuum of strategies to respond to inappropriate behaviors' got the lowest scores from both the instructors and their students corresponding only to 'occasionally'. Analysis of variance showed that the only CMP affected by the length of teaching is the practice of 'prompting students to respond'. Based on the findings, some recommendations for the instructors to improve on the critical feature where they scored low are discussed and suggestions are included for future research.

Keywords: classroom management, CMPs, critical features, evidence-based classroom management practices

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Ari Istiany, Guspri Devi Artanti, M. Si

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Based on the results Riskesdas, it is known that breastfeeding awareness about the importance of exclusive breastfeeding is still low at only 15.3 %. These conditions resulted in a very infant at risk for infectious diseases, such as diarrhea and acute respiratory infection. Therefore, the aim of this study to evaluate the video development about exclusive breastfeeding as a nutrition education media for posyandu cadre. This research used development methods for making the video about exclusive breastfeeding. The study was conducted in urban areas Rawamangun, East Jakarta. Respondents of this study were 1 media experts from the Department of Educational Technology - UNJ, 2 subject matter experts from Department of Home Economics - UNJ and 20 posyandu cadres to assess the quality of the video. Aspects assessed include the legibility of text, image display quality, color composition, clarity of sound, music appropriateness, duration, suitability of the material and language. Data were analyzed descriptively likes frequency distribution table, the average value, and deviation standard. The result of this study showed that the average score assessment according to media experts, subject matter experts, and posyandu cadres respectively was 3.43 ± 0.51 (good), 4.37 ± 0.52 (very good) and 3.6 ± 0.73 (good). The conclusion is on exclusive breastfeeding video as feasible as a media for nutrition education. While suggestions for the improvement of visual media is multiply illustrations, add material about the correct way of breastfeeding and healthy baby pictures.

Keywords: exclusive breastfeeding, posyandu cadre, video, nutrition education

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Ashfaque Hossain Khan, Brian Thomson, Ratan Debnath, Abhishek Motayed, Mulpuri V. Rao

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Though the efforts had been made, the problem of cross-sensitivity for a single metal oxide-based sensor can’t be fully eliminated. In this work, a sensor array has been designed and fabricated comprising of platinum (Pt), copper (Cu), and silver (Ag) decorated TiO2 and ZnO functionalized GaN nanowires using industry-standard top-down fabrication approach. The metal/metal-oxide combinations within the array have been determined from prior molecular simulation study using first principle calculations based on density functional theory (DFT). The gas responses were obtained for both single and mixture of NO2, SO2, ethanol, and H2 in the presence of H2O and O2 gases under UV light at room temperature. Each gas leaves a unique response footprint across the array sensors by which precise discrimination of cross-sensitive gases has been achieved. An unsupervised principal component analysis (PCA) technique has been implemented on the array response. Results indicate that each gas forms a distinct cluster in the score plot for all the target gases and their mixtures, indicating a clear separation among them. In addition, the developed array device consumes very low power because of ultra-violet (UV) assisted sensing as compared to commercially available metal-oxide sensors. The nanowire sensor array, in combination with PCA, is a potential approach for precise real-time gas monitoring applications.

Keywords: cross-sensitivity, gas sensor, principle component analysis (PCA), sensor array

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Authors: Ahmed A. Lugard, Mohammed A. Aliyu

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This paper studied the influence of urban development and its accompanied land surface transformation on sediment concentration of a natural flowing Ginzo river across the city of Katsina. An opposite twin river known as Tille river, which is less urbanized, was used to compare the result of the sediment concentration of the Ginzo River in order to ascertain the consequences of the urban area on impacting the sediment concentration. An instrument called USP 61 point integrating cable way sampler described by Gregory and walling (1973), was used to collect the suspended sediment samples in the wet season months of June, July, August and September. The result obtained in the study shows that only the sample collected at the peripheral site of the city, which is mostly farmland areas resembles the results in the four sites of Tille river, which is the reference stream in the study. It was found to be only + 10% different from one another, while at the other three sites of the Ginzo which are highly urbanized the disparity ranges from 35-45% less than what are obtained at the four sites of Tille River. In the generalized assessment, the t-distribution result applied to the two set of data shows that there is a significant difference between the sediment concentration of urbanized River Ginzo and that of less urbanized River Tille. The study further discovered that the less sediment concentration found in urbanized River Ginzo is attributed to concretization of surfaced, tarred roads, concretized channeling of segments of the river including the river bed and reserved open grassland areas, all within the catchments. The study therefore concludes that urbanization affect not only the hydrology of an urbanized river basin, but also the sediment concentration which is a significant aspect of its geomorphology. This world certainly affects the flood plain of the basin at a certain point which might be a suitable land for cultivation. It is recommended here that further studies on the impact of urbanization on River Basins should focus on all elements of geomorphology as it has been on hydrology. This would make the work rather complete as the two disciplines are inseparable from each other. The authorities concern should also trigger a more proper environmental and land use management policies to arrest the menace of land degradation and related episodic events.

Keywords: environment, infiltration, river, urbanization

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Authors: A. Sathiya Susuman, Hamisi F. Hamisi

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Background: Many socio-economic and demographic data are age-sex attributed. However, a variety of irregularities and misstatement are noted with respect to age-related data and less to sex data because of its biological differences between the genders. Noting the misstatement/misreporting of age data regardless of its significance importance in demographics and epidemiological studies, this study aims at assessing the quality of 2012 Tanzania Population and Housing Census Results. Methods: Data for the analysis are downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple’s index, Myers’ blended index, and Age-Sex Accuracy index. Results: The recorded Whipple’s index for both sexes was 154.43; male has the lowest index of about 152.65 while female has the highest index of about 156.07. For Myers’ blended index, the preferences were at digits ‘0’ and ‘5’ while avoidance were at digits ‘1’ and ‘3’ for both sexes. Finally, Age-sex index stood at 59.8 where sex ratio score was 5.82 and age ratio scores were 20.89 and 21.4 for males and female respectively. Conclusion: The evaluation of the 2012 PHC data using the demographic techniques has qualified the data inaccurate as the results of systematic heaping and digit preferences/avoidances. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.

Keywords: age heaping, digit preference/avoidance, summary indices, Whipple’s index, Myer’s index, age-sex accuracy index

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: Xiao Yang, Ji Zhang, Yingli Song, Hui Huang, Jing Zhang, Yan Wang, Rongrong Han, Zhixuan Xiang, Lu Chen, Lingling Gao

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Aim and Objectives: To examine physical activity self-efficacy, identify its predictors, and further explore the mechanism of action among the predictors in mainland Chinese pregnant women with high risk for gestational diabetes mellitus (GDM). Background: Physical activity could protect pregnant women from developing GDM. Physical activity self-efficacy was the key predictor of physical activity. Design: A cross-sectional study was conducted from October 2021 to May 2022 in Zhengzhou, China. Methods: 252 eligible pregnant women completed the Pregnancy Physical Activity Self-efficacy Scale, the Social Support for Physical Activity Scale, the Knowledge on Physical Activity Questionnaire, the 7-item Generalized Anxiety Disorder scale, the Edinburgh Postnatal Depression Scale, and a socio-demographic data sheet. Multiple linear regression was applied to explore the predictors of physical activity self-efficacy. Structural equation modeling was used to explore the mechanism of action among the predictors. Results: Chinese pregnant women with a high risk for GDM reported a moderate level of physical activity self-efficacy. The best-fit regression analysis revealed four variables explained 17.5% of the variance in physical activity self-efficacy. Social support for physical activity was the strongest predictor, followed by knowledge of the physical activity, intention to do physical activity, and anxiety symptoms. The model analysis indicated that knowledge of physical activity could release anxiety and depressive symptoms and then increase physical activity self-efficacy. Conclusion: The present study revealed a moderate level of physical activity self-efficacy. Interventions targeting pregnant women with high risk for GDM need to include the predictors of physical activity self-efficacy. Relevance to clinical practice: To facilitate pregnant women with high risk for GDM to engage in physical activity, healthcare professionals may find assess physical activity self-efficacy and intervene as soon as possible on their first antenatal visit. Physical activity intervention programs focused on self-efficacy may be conducted in further research.

Keywords: physical activity, gestational diabetes, self-efficacy, predictors

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Authors: Sharareh Hekmat, Michelle Lane

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Pregnancy during adolescence affects both the growth and development of mother and baby, particularly in low socioeconomic and food insecure areas. This mixed methods study is aimed at discovering a need for a community-based probiotic yogurt program to assist pregnant women in the Mukuru slum Nairobi, Kenya. Surveys were conducted with pregnant women (14-25 years old, n=43), which included questionnaires on dietary intake, food access, and health/quality of life perception. The frequency and means procedure was used to analyze maternal characteristics, Women’s Dietary Diversity Score (WDDS) and Household Hunger Scale. 24-hour recalls were analyzed via ESHA Food Processor, and median nutrient intakes were reported as a percent of recommendations. An environmental scan was conducted to assess food availability, accessibility, and quality. WDDS reflected a low-moderate diet variation (3.86 food groups out of 9, SD ± 1.3) among the women. The 24-hour recall suggested an inadequate intake of many nutrients, most significantly B12, potassium and calcium. 86% of women reported little to no household hunger. However, the environmental scan revealed low quality and poor sanitation of food. This study provides evidence that a probiotic program would be desirable, and contribute to the nutritional status of women in the Mukuru community.

Keywords: dietary diversity, pregnant women, probiotics, urban slum, Kenya

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Authors: Eldah Ephraim Buba, Sanusi Abubakar Sadiq

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Habitat can be degraded by tourism leisure activities for example wildlife viewing can bring abrupt stress for animals and alter their natural behaviors when tourist come too close and wildlife watching have degradation effects on the habitats as they often are accompanied by the noise and commotion created by tourist as they chase wild animals. It is observed that Jos Wild Life Park is usually congested during on-peak periods which causes littering and contamination of the environment by tourist which may lead to changes in the soil nutrient. The issue of unauthorized feeding of animals by a tourist in which the food might be dangerous and harmful to their health and making them be so aggressive is also observed. The aim of the study is to investigate the environmental impact of tourists’ activities in Jos Wild Life Park, Nigeria. The study used survey questionnaires to both tourists and the staff of the wildlife park. One hundred questionnaires were self-administered to randomly selected tourists as the visit the park and some staff. The average mean score of the response was used to show agreement or disagreement. Major findings show the negative impact of tourist’s activities to the environment as air pollution, overcrowding, and congestion, solid littering of the environment, distress to animals and alteration of the ecosystem. Furthermore, the study found the positive impact of tourists activities on the environment to be income generation through tourists activities and infrastructural development. It is recommended that the impact of tourism should be minimized through admitting the right carrying capacity and impact assessment.

Keywords: environmental, impact, investigation, tourists, activities

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Authors: P. Efstathiou, E. Kouskouni, S. Papanikolaou, K. Karageorgou, Z. Manolidou, Tseroni Maria, A. Efstathiou, V. Karyoti, I. Agrafa

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Aim: Aim of this study was to evaluate the reduction on Intensive Care Unit (ICU) microbial flora after the antimicrobial copper alloy (Cu+) implementation as well as the effect on financial-epidemiological operation parameters. Methods: Medical, epidemiological and financial data in two time periods, before and after the implementation of copper (Cu 63% - Zn 37%, low lead) were recorded and analyzed in a general ICU. The evaluated parameters were: the importance of patients' admission (Acute Physiology and Chronic Health Evaluation - APACHE II and Simplified Acute Physiology Score - SAPS), microbial flora's record in the ICU before and after the implementation of Cu+ as well as the impact on epidemiological and ICU's operation financial parameters. Results: During December 2010 and March 2011 and respectively during December 2011 and March 2012 comparative results showed statistically significant reduction on the microbial flora (CFU/ml) by 95% and the use of antimicrobial medicine (per day per patient) by 30% (p = 0,014) as well as patients hospitalization time and cost. Conclusions: The innovative implementation of antimicrobial copper in ICUs contributed to their microbial flora significant reduction and antimicrobial drugs use reduction with the apparent positive effect (decrease) in both patient’s hospitalization time and cost. Under the present circumstances of economic crisis, survey results are of highest importance and value.

Keywords: antimicrobial copper, financial benefits, ICU, cost reduction

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Authors: Nwobu Obiamaka, Owolabi Akintola

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This study examined the extent of statistical significant difference between the economic, environmental, governance and social aspects of sustainability reporting as a result of board committee on sustainability and time (year) of reporting for business organizations in the Nigerian banking sector. The years of reporting under consideration were 2010, 2011, 2012 and 2013. Content analysis methodology was employed through a reporting index used to score the amount of economic, environmental, governance and social indicators of sustainability reporting. The results of this study indicated that business organizations with board committee on sustainability had more indicators of sustainability reporting than those without board committees on sustainability issues. Also, sustainability reporting in 2013 was higher than that of prior years (2012, 2011 and 2010) for the economic, environmental and social indicators. The governance indicators of 2012 was highest compared to the other years (2013, 2011 and 2010) under consideration in this study. The implication of this finding is that business organizations that have board committees on sustainability are monitored by such boards to report more to their stakeholders. On the other hand, business organizations are appreciating the need to engage in sustainability reporting with each passing year. This could be due to the Central Bank of Nigeria (CBN) Sustainability Reporting framework that business organizations in the banking sector have to adhere to. When sustainability issues are monitored from the board of directors, business organizations are likely to increase and improve on their sustainability reporting.

Keywords: governance, organizations, reporting, sustainability

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Authors: Priyanka Sharma, Tarkewshwar Dubey, Hemalatha Siva

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Hemorrhoids are one of the most common anorectal diseases around the world. Severalfactors are involved in causing hemorrhoids including irregularbowel function (constipation, diarrhea), exercise, gravity, low fiberdiet, pregnancy, obesity, high abdominal pressure, prolongedsitting, genetic factors, and aging. Pain, bleeding, itching,swelling and anal discharge are the symptoms of the disease. Due to limitedmodern pharmacotherapeutic options available for treatment, theherbal medicines remain the choice of therapy. Blumea lacera (Burm f.) DC. belonging to the Asteraceae family is a common plain land weed of Bangladesh. Traditionally it has been used for treatment of hemorrhoids.Considering the above fact, present study was aimed to validate the ethnomedicinal use of B. lacera leaves on experimental hemorrhoids in rats. The anti-hemorrhoid activity was performed by using croton oil induced rat models. The parameters studied were assessment of TNF-α and IL-6, Evans blue exudation, macroscopic severity score, recto-anal coefficient, histomorphological scores. Also, in vivo antioxidant parameters and histopathological studies were also performed. All paramaters exhibited significant anti-hemorrhoid activity. Moreover ethanolic extract of B. lacera (EBL) leaves 400mg/kg showed ameliorative effect oncroton oil induced hemorrhoids.In conclusion, EBL exhibitedbeneficial effect on croton oil- induced hemorrhoids and validates its ethnomedicinal use in treatment of piles.

Keywords: haemorrhoids, IL-6, piles, TNF-α

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Authors: Maryam Zarra-Nezhad, Ali Moazami-Goodarzi, Joona Muotka, Nina Sajaniemi

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This study examines the extent to which the impact of a universal intervention program, i.e., POMPedaSens, on children’s early social-emotional learning (SEL) is different depending on early childhood education (ECE) teaches stress at work. The POMPedaSens program aims to promote children’s (5–6-year-olds) SEL by supporting ECE teachers’ engagement and emotional availability. The intervention effectiveness has been monitored using an 8-month randomized controlled trial design with an intervention (IG; 26 teachers and 195 children) and a waiting control group (CG; 36 teachers and 198 children) that provided the data before and after the program implementation. The ECE teachers in the IG are trained to implement the intervention program in their early childhood education and care groups. Latent change score analysis suggests that the program increases children’s prosocial behavior in the IG when teachers show a low level of stress. No significant results were found for the IG regarding a change in antisocial behavior. However, when teachers showed a high level of stress, an increase in prosocial behavior and a decrease in antisocial behavior were only found for children in the CG. The results suggest a promising application of the POMPedaSens program for promoting prosocial behavior in early childhood when teachers have low stress. The intervention will likely need a longer time to display the moderating effect of ECE teachers’ well-being on children’s antisocial behavior change.

Keywords: early childhood, social-emotional learning, universal intervention program, professional development, teachers' stress

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Authors: Peien Ma

Abstract:

Bilingual effect/advantage theorized the positive effect of being bilingual on general cognitive abilities, but it was unknown which factors tend to modulate these bilingualism effects on working memory capacity. This study imposed empirical field research on a group of low-SES emerging bilinguals, Miao people, in the hill tribes of rural China to investigate whether bilingualism affected their verbal working memory performance. 20 Miao-Chinese bilinguals (13 girls and 7 boys with a mean age of 11.45, SD=1.67) and 20 Chinese monolingual peers (13 girls and 7 boys with a mean age of 11.6, SD=0.68) were recruited. These bilingual and monolingual juveniles, matched on age, sex, socioeconomic status, and educational status, completed a language background questionnaire and a standard forward and backward digit span test adapted from Wechsler Adult Intelligence Scale-Revised (WAIS-R). The results showed that bilinguals earned a significantly higher overall mean score of the task, suggesting the superiority of working memory ability over the monolinguals. And bilingual cognitive benefits were independent of proficiency levels in learners’ two languages. The results suggested that bilingualism enhances working memory in sequential bilinguals from low SES backgrounds and shed light on our understanding of the bilingual advantage from a psychological and social perspective.

Keywords: bilingual effects, heritage language, Miao/Hmong language Mandarin, working memory

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Authors: A. S. Haruna, M. L. Mayanchi

Abstract:

Pre Nigeria Certificate in Education otherwise called Pre-NCE is an intensive two semester course designed to assist candidates who could not meet the requirements for admission into NCE programme. The task of coping with the stressors in the course can interfere with the students’ ability to regulate attention skills and stay organized. The main objectives of the study were to find out the prevalence of stress; determine the association between stress and ADD and reveal gender difference in the prevalence of ADD among stressed pre-NCE students. Cross–Sectional Correlation Design was employed in which 333 (Male=65%; Female=35%) students were proportionately sampled and administered Stress Assessment Scale [SAS r=0.74) and those identified with stress were thereafter rated with Cognitive Processing Inventory [CPI]. Data collected was used to analyze the three null hypotheses through One-sample Kolmogorov-Smirnov (K-S) Z-score, Pearson Product Moment Correlation Coefficients (PPMCC) and t-test statistics respectively at 0.05 confidence level. Results revealed significant prevalence of stress [Z-calculated =2.24; Z-critical = ±1.96], and a positive relationship between Stress and ADD among Pre-NCE students [r-calculated =0.450; r-critical =0.138]. However, there was no gender difference in the prevalence of ADD among stressed Pre-NCE students in the college [t-calculated =1.49; t-critical =1.645]. The study concludes that while stress and ADD prevail among pre-NCE students, there was no gender difference in the prevalence of ADD. Recommendations offered suggest the use of Learners Assistance Programs (LAP) for stress management, and Teacher-Students ratio of 1:25 be adopted in order to cater for stressed pre-NCE students with ADD.

Keywords: attention deficit disorder, pre-NCE students, stress, Pearson Product Moment Correlation Coefficients (PPMCC)

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Authors: Shahrzad Yektatalab, Agrin Mohammadi, Ladan Zarshenas

Abstract:

Background: Misophonia is a severe emotional response to repetitive sounds. This disorder may limit a person's communication, reduce their ability, or disrupt their social and personal life. This study aims to determine the prevalence of Misophonia and its relationship with obsessive-compulsive disorder, anxiety, and depression in undergraduate students of XXX University of Medical Sciences. Methods: The present study is an analytical descriptive study conducted in October 2020. The study samples are 390 undergraduate students of XXX University of medical sciences. A relative and systematic sampling method was used. In this study, a demographic questionnaire, misophonia questionnaire (A score of 7 or higher is considered as misophonia), Beck anxiety questionnaire, Beck depression questionnaire, and Maudsley questionnaire were used, and the data were analyzed using SPSS 24 software. Due to the non-normality of the data, the Spearman correlation coefficient was used for analyzing data. The significance level was considered less than 0.05. Results: 23.8% of students have misophonia. Of the 390 participants in the study, 93 had experienced misophonia. Among these 93 students, 37 (39.8%) had obsessive-compulsive disorder, 8 (8.6%) had anxiety and 9 (9.7%) had depression. There was a significant and direct relationship between all variables (p <0.001), which means that with the increase of each disorder, the probability of an increase in other disorders increases. Conclusion: Due to the high prevalence of misophonia in students and its direct relationship with obsessive-compulsive disorder, anxiety, and depression, It is recommended that future studies be conducted to identify ways to prevent and reduce the incidence of misophonia.

Keywords: misophonia, obsessive-compulsive disorder, anxiety, depression

Procedia PDF Downloads 55

Authors: Manoj Kumar, Sujata Mohanty, D. N. Rao, Arul Selvi, Sanjeev K. Bhoi

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Background: Hematopoietic progenitor cells (HPC) mobilized from bone marrow to peripheral blood has been observed in severe trauma and hemorrhagic shock patients. Granulocyte-colony stimulating factor (G-CSF) is a potent stimulator that mobilized HPC from bone marrow to peripheral blood. Objective: Our aim of the study was to investigate the serum G-CSF levels and correlate with HPC and outcome. Methods: Peripheral blood sample from 50 hemorrhagic shock patients was collected on arrival for determination of G-CSF and peripheral blood HPC (PBHPC) and compared with healthy control (n=15). Determination of serum levels of G-CSF by sandwich ELISA and PBHPC by Sysmex XE-2100. Data were categorized by age, sex, Injury Severity Score (ISS), and laboratory data was prospectively collected. Data are expressed as mean±SD and median (min, max). Results: Significantly increased the serum level of G-CSF (264.8 vs. 79.1 pg/ml) and peripheral blood HPC (0.1 vs. 0.01 %) in the T/HS patients when compared with control group. Conclusions: Our studies suggest serum G-CSF elevated in T/HS patients. The elevated in G-CSF was also associated with mobilization of HPC from BM to peripheral blood HPC. Increased the levels of G-CSF in T/HS may play a significant role in the alteration of the hematopoietic compartment.

Keywords: granulocyte colony stimulating factor, G-CSF, hematopoietic progenitor cells, HPC, trauma hemorrhagic shock, T/HS, outcome

Procedia PDF Downloads 324

Authors: Anupam Sibal

Abstract:

Whatever is measured tends to improve. With a view to objectively measuring and improving clinical quality across the Apollo Group Hospitals, the initiative of ACE @ 25 (Apollo Clinical Excellence@25) was launched on Jan 09. ACE @ 25 is a clinically balanced scorecard incorporating 25 clinical quality parameters involving complication rates, mortality rates, one-year survival rates and average length of stay after major procedures like liver and renal transplant, CABG, TKR, THR, TURP, PTCA, endoscopy, large bowel resection and MRM covering all major specialties. Also included are hospital acquired infection rates, pain satisfaction and medication errors. Benchmarks have been chosen from the world’s best hospitals. There are weighted scores for outcomes color coded green, orange and red. The cumulative score is 100. Data is reported monthly by 43 Group Hospitals online on the Lighthouse platform. Action taken reports for parameters falling in red are submitted quarterly and reviewed by the board. An audit team audits the data at all locations every six months. Scores are linked to appraisal of the medical head and there is an “ACE @ 25” Champion Award for the highest scorer. Scores for different parameters were variable from green to red at the start of the initiative. Most hospitals showed an improvement in scores over the last four years for parameters where they had showed scores in red or orange at the start of the initiative. The overall scores for the group have shown an increase from 72 in 2010 to 81 in 2015.

Keywords: benchmarks, clinical quality, lighthouse, platform, scores

Procedia PDF Downloads 296

Authors: Rula D. Alshareef, Safa S. Alqathmi, Ghadah K. Alkhouldi, Reem O. Bagabas, Farheen B. Hasan

Abstract:

Safety engineering is among the most crucial considerations in any work environment. Providing mentally, physically, and environmentally safe work conditions must be the top priority of any successful organization. Company X is a local paint production company in Saudi Arabia; in a month, the factory experienced two significant accidents, which indicates that workers’ safety is overlooked. The aim of the research is to examine the risks, assess the root causes and recommend control measures that will eventually contribute to providing a safe workplace. The methodology used is sectioned into three phases, risk identification, assessment, and finally, mitigation. In the identification phase, the team used Rapid Entire Body Assessment (REBA) and National Institute for Occupational Safety and Health Lifting Index (NIOSH LI) tools to holistically establish knowledge about the current risk posed to the factory. The physical hazards in the factory were assessed in two different operations, which are mixing and filling/packaging. For the risk assessment phase, the hazards were deeply analyzed through their severity and impact. Additionally, through risk mitigation, the Rapid Entire Body Assessment (REBA) score decreased from 11 to 7, and the National Institute for Occupational Safety and Health Lifting Index (NIOSH LI) has been reduced from 5.27 to 1.85.

Keywords: ergonomics, safety, workplace risks, hazards, awkward posture, fatigue, work environment

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Authors: Tariq Ali Gujar, Anita Hökelmann

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Postural balance plays essential role throughout life in daily activities. Somatosensory, visual and vestibular inputs play the fundamental role in maintaining body equilibrium to balance the posture. The aim of this study was to find out electroencephalography (EEG) responses during balance activity of young people during Sensory Organization Balance Test. The outcome of this study will help to create the fitness and neurorehabilitation plan. 25 young people (25 ± 3.1 years) have been analyzed on Balance Master NeuroCom® with the coupling of Brain Vision 32 electrode wireless EEG system during the Sensory Organization Test. From the results it has been found that the balance score of samples is significantly higher under the influence of somatosensory input as compared to visual and vestibular input (p < 0.05). The EEG between somatosensory and visual input to balance the posture showed significantly higher (p < 0.05) alpha and beta activities during somatosensory input in somatosensory, attention and visual functions of the cortex whereas executive and motor functions of the cerebral cortex showed significantly higher (p < 0.05) alpha EEG activity during the visual input. The results suggest that somatosensory and attention function of the cerebral cortex has alpha and beta activity, respectively high during somatosensory and vestibular input in maintaining balance. In patients with balance impairments both physical and cognitive training, including neurofeedback will be helpful to improve balance abilities.

Keywords: balance, electroencephalography activity, somatosensory, visual, vestibular

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Authors: Pablo Cid Galache, Laura Zamorano Bonilla

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Mauriac syndrome (MS) is a rare complication of type 1 diabetes mellitus (DM1). It is rela-ted to low insulin concentrations. Therefore is a complication mainly found in developing countries. The main clinical features are hepatomegaly, edema, growth and puberty delay, and the presence of elevated transaminases and serum lipids. The MS incidence is de-creasing due to the new types of insulin and intensive glycemic control. Therefore is a rare diagnosis in Europe nowadays, being described mainly in developing countries or with so-cioeconomic limitations to guarantee an adequate management of diabetes. Edema secondary to fluid retention is a rare complication of insulin treatment, especially in young patients. Its severity is variable and is mainly related to the start of a proper treatment and the improvement in glycemic control after diagnosis or after periods of poor metabolic control. Edema resolves spontaneously without requiring treatment in most cases. The Pediatric Endocrinology Unit of Hospital Motril could diagnose a 14-year-old girl who presented very poor metabolic control during the last 3 years as a consequence of the socioeconomic conditions of the country of origin during the last years. Presents up to 4 admissions for ketoacidosis during the last 12 months. After the family moved to Spain our patient began to be followed up in our Hospital. Initially presented glycated hemoglobin figures of 11%. One week after the start of treatment, the patient was admitted in the emergency room due to the appearance of generalized edema and pain in the limbs. The main laboratory abnormalities include: blood glucose 225mg/dl; HbA1C 10.8% triglycerides 543 mg/dl, total cholesterol 339 mg/dl (LDL 225) GOT 124 U/l, GPT 89U/l. Abdominal ultrasound shows mild hepatomegaly and no signs of ascites were shown. The patient presented a progressive improvement with resolution of the edema and analitical abnormalities during the next two weeks. During admission, the family received diabetes education, achieving adequate glycemic control at discharge. Nowadays the patient has a good glycemic control having glycated hemoglobin levels around 7%.

Keywords: Mauriac, diabetes, complication, developing countries

Procedia PDF Downloads 49

Authors: Rajani S. Pujar, Pandurangarao N. Kulkarni

Abstract:

Increased temporal masking affects the speech perception in persons with sensorineural hearing impairment especially under adverse listening conditions. This paper presents a cascaded scheme, which employs a noise reduction algorithm as well as temporal splitting of the speech signal. Earlier investigations have shown that by splitting the speech temporally and presenting alternate segments to the two ears help in reducing the effect of temporal masking. In this technique, the speech signal is processed by two fading functions, complementary to each other, and presented to left and right ears for binaural dichotic presentation. In the present study, half cosine signal is used as a fading function with crossover gain of 6 dB for the perceptual balance of loudness. Temporal splitting is combined with noise reduction algorithm to improve speech perception in the background noise. Two noise reduction schemes, namely spectral subtraction and Wiener filter are used. Listening tests were conducted on six normal-hearing subjects, with sensorineural loss simulated by adding broadband noise to the speech signal at different signal-to-noise ratios (∞, 3, 0, and -3 dB). Objective evaluation using PESQ was also carried out. The MOS score for VCV syllable /asha/ for SNR values of ∞, 3, 0, and -3 dB were 5, 4.46, 4.4 and 4.05 respectively, while the corresponding MOS scores for unprocessed speech were 5, 1.2, 0.9 and 0.65, indicating significant improvement in the perceived speech quality for the proposed scheme compared to the unprocessed speech.

Keywords: MOS, PESQ, spectral subtraction, temporal splitting, wiener filter

Procedia PDF Downloads 320