Search results for: residual life prediction

Authors: Urbi Pal, Piyas Palit, Jitendra Mathur, Abhay Chaturvedi, Sandip Bhattacharya

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The hot rolled slab lifting crane cable reel drum (CRD) failed due to failure of cable reel flat spring which are inside the cassette of CRD. CRD is used for the movement of tong cable. Stereoscopic observation revealed beach marks and Scanning Electron Microscopy showed striations confirming fatigue mode of failure. Chemical composition should be spring steel (Cr-Mo-V) as per IS 3431:1982 instead of C-Mn steel. To find out the reason of fatigue failure, the theoretical fatigue life of flat spiral spring has been calculated. The calculation of number of fatigue cycles included bending moment, maximum stress on the spring, ultimate tensile strength and alternative stress. The bending moment determination has been taken account with various parameters like Young’s Modulus, width, thickness, outer diameter, arbor diameter, pay out the length and angular deflection in rotations. With all the required data, the calculated fatigue life turned to be 10000 cycles, but the spring served 15000 cycles which clearly indicated beyond fatigue life usage. Different UTS values have been plotted with respect to the number of fatigue cycles and clearly showed that the increase in UTS by 40% increases fatigue life by 50%. The significance of higher UTS lied here, and higher UTS depends on modified chemistry with proper tempered martensite microstructure. This kind of failure can be easily avoided by changing the crane spring maintenance schedule from 2 years to 1.5 years considering 600 cycles per month. The plant has changed changing the schedule of cable reel spring and procured new flat reel spring made of 50CrV2 steel.

Keywords: cable reel spring, fatigue life, stress, spring steel

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Authors: Chiou-Fang Liou

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Cancer has been one of the most life-threaten diseases worldwide for 30+ years. The influences of cancer illness include symptoms from cancer itself along with its treatments. The quality of life among patients diagnosed with cancer during cancer treatments has been conceptualized within four domains: Functional Well-Being, Social Well-Being, Physical Well-Being, and Emotional Well-Being. Patients with cancer often need to make adjustments to face all the challenges. The middle-range theory of Resourcefulness and Quality of life has been applied to explore factors contributing to cancer patients’ needs. Resourcefulness is defined as sets of skills that can be learned and consisted of Person and Social Resourcefulness. Empirical evidence also supported a possible relationship between Resourcefulness and Quality of Life. However, little is known about the extent to which the two concepts are related to each other. This study, therefore, applied a multivariate technique, Canonical Correlation Analysis, to identify the relationship between the two sets of variables with multi-dimensional measures, the Resourcefulness and Quality of Life in Cancer patients receiving treatments. After IRB approval, this multi-centered study took place at two medical centers in the Central Region of Taiwan. Sample A total of 186 patients with various cancer diagnoses and either receiving radiation therapy or chemotherapy consented to and answered questionnaires. The Import findings of the Generalized F test identified two typical sets with several linear relations and explained a total of 79.1% of the total variance. The first typical set found Personal Resourcefulness negatively related to Social Well-being, Functional being, Emotional Well-being, and Physical, in that order. The second typical set found Social Resourcefulness negatively related to Functional Well-being and Physical-being yet positively related to Social Well-being and Emotional Well-being. Discussion and Conclusion, The results of this presented study supported the statistically significant relationship between two sets of variables that are consistent with the theory. In addition, the results are considerably important in cancer patients receiving cancer treatments.

Keywords: cancer, canonical correlation analysis, quality of life, resourcefulness

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Authors: Muhammad Ahsan

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The effective decommissioning of oil and gas fields and related assets is one of the most important challenges facing the oil and gas industry today and in the future. Decommissioning decisions can no longer be avoided by the operators and the industry as a whole. Decommissioning yields no return on investment and carries significant regulatory liabilities. The main objective of this paper is to provide an approach and mechanism for the estimation of emissions associated with decommissioning of Oil and Gas fields. The model uses gate to gate approach and considers field life from development phase up to asset end life. The model incorporates decommissioning processes which includes; well plugging, plant dismantling, wellhead, and pipeline dismantling, cutting and temporary fabrication, new manufacturing from raw material and recycling of metals. The results of the GHG emissions during decommissioning phase are 2.31x10-2 Kg CO2 Eq. per Mcf of the produced natural gas. Well plug and abandonment evolved to be the most GHG emitting activity with 84.7% of total field decommissioning operational emissions.

Keywords: LCA (life cycle analysis), gas field, decommissioning, emissions

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Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

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Authors: Thimira Pasas P, Nirmala Priyadarshani M, Ishani R

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Obesity is a global health issue. Early identification is essential to plan interventions and intervene than to reduce the worsening of obesity and its consequences on the health issues of the individual. Childhood obesity is multifactorial, with both modifiable and unmodifiable risk factors. A genetically susceptible individual (unmodifiable), when placed in an obesogenic environment (modifiable), is likely to become obese in onset and progression. The present study was conducted to identify the age of onset of childhood obesity and the influence of modifiable risk factors for childhood obesity among school children living in a suburban area of Sri Lanka. The study population was aged 11-12 years of Piliyandala Educational Zone. Data were collected from 11–12-year-old school children attending government schools in the Piliyandala Educational Zone. They were using a validated, pre-tested self-administered questionnaire. A stratified random sampling method was performed to select schools and to select a representative sample to include all 3 types of government schools of students due to the prevailing pandemic situation, information from the last school medical inspection on data from 2020used for this purpose. For each obese child identified, 2 non-obese children were selected as controls. A single representative from the area was selected by using a systematic random sampling method with a sampling interval of 3. Data was collected using a validated, pre-tested self-administered questionnaire and the Child Health Development Record of the child. An introduction, which included explanations and instructions for filing the questionnaire, was carried out as a group activity prior to distributing the questionnaire among the sample. The results of the present study aligned with the hypothesis that the age of onset of childhood obesity and prediction must be within the first two years of child life. A total of 130 children (66 males: 64 females) participated in the study. The age of onset of obesity was seen to be within the first two years of life. The risk of obesity at 11-12 years of age was Obesity risk was identified at 3-time s higher among females who underwent rapid weight gain within their infancy period. Consuming milk prior to breakfast emerged as a risk factor that increases the risk of obesity by three times. The current study found that the drink before breakfast tends to increase the obesity risk by 3-folds, especially among obese females. Proper monitoring must be carried out to identify the rapid weight gain, especially within the first 2 years of life. Consumption of mug milk before breakfast tends to increase the obesity risk by 3 times. Identification of the confounding factors, proper awareness of the mothers/guardians and effective proper interventions need to be carried out to reduce the obesity risk among school children in the future.

Keywords: childhood obesity, school children, age of onset, weight gain, feeding pattern, activity level

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Jenny Oliveros Lao Phillips, Arturo E. Osorio, José Alves

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Family business are the dominant form of business in the world, and Chinese family business (CFB) is a unique type of family business that relies on collective action to survive. This paper argues that in CFBs, entrepreneurial actions are transgenerational collective endeavors, and successors are groomed as stewards of the family legacy. Work-life relationship in CFBs is about synergy and not balance because the family identity is the business identity, and vice-versa. Using five in-depth case studies, this research introduces an alternative understanding of CFBs and proposes a model of work-life synergy in transgenerational entrepreneurship based on discussion of five theory-based propositions. This model explains that through emphasizing on the business family’s shared value and entrepreneurial legacy, elements of trust, shared identity and stewardship of family members are enhanced which leads to collective action and goal of the business family, resulting in transgenerational entrepreneurship. Limitations and future research are presented.

Keywords: Chinese family business, family legacy, stewardship, transgenerational entrepreneurship, work-life synergy

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Authors: Nazia Mustafa, Aneela Maqsood

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Pediatric Quality of Life Inventory is the most widely used instrument for assessing children and adolescent health-related quality of life and has shown excellent markers of reliability and validity. The current study was carried out with the objectives of translation and cross-language validation along with the determination of factor Structure and psychometric properties of the Urdu version. It was administered on 154 Primary School Children with age range 10 to12 years (M= 10.86, S.D = 0.62); including boys (n=92) and girls (n = 62). The sample was recruited from two randomly selected schools from the Rawalpindi district of Pakistan. Results of the pilot phase revealed that the instrument had good reliability (Urdu Version α = 0.798; English Version α = 0.795) as well as test-retest correlation coefficients over a period of 15 days (r = 0.85). Exploratory factor analysis (EFA) resulted in three factorial structures; Social/School Functioning (k = 8), Psychological Functioning (k = 7) and Physical Functioning (k = 6) considered suitable for our sample instead of four factors. Bartlett's test of sphericity showed inter-correlation between variables. However, factor loadings for items 22 and 23 of the School Functioning subscale were problematic. The model was fit to the data after their removal with Cronbach’s Alpha Reliability coefficient of the scale (k = 21) as 0.87 and for subscales as 0.75, 0.77 and 0.73 for Social/School Scale, Psychological subscale and Physical subscale, respectively. These results supported the feasibility and reliability of the Urdu version of the Pediatric Quality of Life Inventory as a reliable and effective tool for the measurement of quality of life among Pediatrics Pakistani population.

Keywords: primary school children, paediatric quality of life, exploratory factor analysis, Pakistan

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

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Authors: Rafik Balti, Nourhene Zayoud, Mohamed Ben Mansour, Abdellah Arhaliass, Anthony Masse

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Application of edible films and coatings with natural active compounds for enhancing storage stability of food products is a promising active packaging approach. Shrimp are generally known as valuable seafood products around the world because of their delicacy and good nutritional. However, shrimp is highly vulnerable to quality deterioration associated with biochemical, microbiological or physical changes during postmortem storage, which results in the limited shelf life of the product. Chitosan is considered as a functional packaging component for maintaining the quality and increasing the shelf life of perishable foods. The present study was conducted to evaluate edible coating of crab chitosan containing variable levels of ethanolic extract of Spirulina on microbiological (mesophilic aerobic, psychrotrophic, lactic acid bacteria, and enterobacteriacea), chemical (pH, TVB-N, TMA-N, PV, TBARS) and sensory (odor, color, texture, taste, and overall acceptance) properties of shrimp during refrigerated storage. Also, textural and color characteristics of coated shrimp were performed. According to the obtained results, crab chitosan in combination with Spirulina extract was very effective in order to extend the shelf life of shrimp during storage in refrigerated condition.

Keywords: food packaging, chitosan, spirulina extract, white shrimp, shelf life

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Authors: Xue Wu

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Since the 1980s, a series of policies and practices have been implemented in China in response to the unprecedented rate of ageing population. The paper provides a detailed narrative of what later-life learning policy discourses have been advocated and gives a description on relevant practical issues during the past three decades. The research process based on the discourse approach with a systematic review of the government-issued documents. It finds that the main practices taken by central government at various levels were making University of the Aged (UA) available in all urban and rural regions to consolidate the newly student enrollments; focusing social-recreational, leisure and cultural activities on 55-75 age group; and utilizing various methods including voluntary works and tourism to improve older adults’ physical and mental wellness. Although there were greater achievements with 30 years of development, many problems still exist. Finding reveals that the curriculum should be modified to meet the needs of the local development, to promote older adults’ contact and contribution to the community, and to enhance technical competences of those in rural areas involving in agricultural production. Central government should also integrate resources from all sectors of the society for further developing later-life learning in China. The result of this paper highlights the value to promote community-based later-life learning for building a society for active ageing and ageing in place.

Keywords: ageing population, China, later-life learning, policy, University of the Aged

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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: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Majid Davoodi Makinejad, Reza Ghaeli

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Developing sustainable and environment-friendly products has become a major concern in the car manufacturing industry. New legislation ‘End of Life Vehicle’ increased design complexities of bumper system parameters e.g. design for disassembly, design for remanufacturing and recycling. ELV processing employs dismantling, shredding and landfill. The bumper is designed to prevent physical damage, reduce aerodynamic drag force as well as being aesthetically pleasing to the consumer. Design for dismantling is the first step in ELVs approach in the bumper system. This study focused on the analysis of ELV value in redesign solutions of the bumper system in comparison with the conventional concept. It provided a guideline to address the critical consideration in material, manufacturing and joining methods of bumper components to take advantages in easy dismounting, separation and recycling.

Keywords: sustainable development, environmental friendly, bumper system, end of life vehicle

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Authors: Priyanka R. Sagar

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Social economic status (SES) is a variable that denotes the social standing of a person in society, and quality of life is a measure of health, happiness, and comfort of an individual. During early 2020, the world was stuck by the blow of the COVID-19 pandemic resulting in minimal or no economic activities to takes place. The present research paper is an attempt to analyze the socioeconomic status and quality of life of construction workers dwelling in the sub-urban areas of Hoskote located in the Bengaluru rural district pre and post-COVID-19. It also tries to analyze the difference in these variables pre and post-COVID-19. The study uses a retrospective design and data collected through a questionnaire survey from the respondents of Hoskote. A total of 100 samples were collected, out of which 73% were men and 27% were women. The mean age group of the participants is 41.04 ± 6.97 years. The overall analysis of the study shows that there is a significant difference in the socioeconomic status of construction workers pre and post-COVID-19. The study shows SES of the workers pre-pandemic is higher than post-pandemic. The other variable is quality of life which consists of physical health, psychological health, social relationships, and environmental domains. The study depicts that the psychological domain alone has been impacted by the pandemic; workers had better mental health pre-COVID-19. The other domains, i.e., physical health, social relationship, and environment, remain unaffected.

Keywords: socio-economic status, quality of life, construction workers, COVID-19

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Authors: Asanka Bulathwatta

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This Study tries to figure out the role of emotional Intelligence for developing coping strategies among adolescents who face traumatic events. Late adolescence students who have enrolled into the University education (Bachelor students/first-year students) would be selected as the sample. University education is an important stage of students’ academic life. Therefore, all students need to develop their competencies to attain the goal of passing examinations and also to developing their wisdom related to the scientific knowledge they gathered through their academic life. Study to be conducted in a cross-cultural manner and it will be taking place in Germany and Sri Lanka. The sample will be consisting of 200 students from each country. Late adolescence is a critical period of the human being as it is foot step in their life which acquiring the emotional and social qualities in their social life. There are many adolescents who have affected by aggression related traumatic events during their lifespan but have not been identified or treated. More specifically, there are numerous burning issues within the first year of the university students namely, ragging done by seniors to juniors, bulling, invalidation and issues raise based on attitudes changes and orientation issues. Those factors can be traumatic for both their academic and day to day lifestyle. Identifying the students who are with emotional damages and their resiliency afterward the aggression related traumas and effective rehabilitation from the traumatic events is immensely needed in order to facilitate university students for their academic achievements and social life within the University education. Research findings in Germany show that students shows more interpersonal traumas, life-threatening illnesses and death of someone related are common in German sample.

Keywords: emotional intelligence, agression, trauma, coping

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: Maria L. G. Lourenço, Keylla H. N. P. Pereira, Viviane Y. Hibaru, Fabiana F. Souza, Joao C. P. Ferreira, Simone B. Chiacchio, Luiz H. A. Machado

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In veterinary medicine, the standard procedure during a caesarian section is clamping the umbilical cord immediately after birth. In human neonates, when the umbilical cord is kept intact after birth, blood continues to flow from the cord to the newborn, but this procedure may prove to be difficult in dogs due to the shorter umbilical cord and the number of newborns in the litter. However, a possible detachment of the placenta while keeping the umbilical cord intact may make the residual blood to flow to the neonate. This study compared the effects on neonatal vitality between clamping and no clamping the umbilical cord of dogs born through cesarean section, assessing them through Apgar and reflex scores. Fifty puppies delivered from 16 bitches were randomly allocated to receive clamping of the umbilical cord immediately (n=25) or to not receive the clamping until breathing (n=25). The neonates were assessed during the first five min of life and once again 10 min after the first assessment. The differences observed between the two moments were significant (p < 0.01) for both the Apgar and reflex scores. The differences observed between the groups (clamped vs. not clamped) were not significant for the Apgar score in the 1st moment (p=0.1), but the 2nd moment was significantly (p < 0.01) in the group not clamped, as well as significant (p < 0.05) for the reflex score in the 1st moment and 2nd moment (p < 0.05), revealing higher neonatal vitality in the not clamped group. The differences observed between the moments (1st vs. 2nd) of each group as significant (p < 0.01), revealing higher neonatal vitality in the 2nd moments. In the no clamping group, after removing the neonates together with the umbilical cord and the placenta, we observed that the umbilical cords were full of blood at the time of birth and later became whitish and collapsed, demonstrating the blood transfer. The results suggest that keeping the umbilical cord intact for at least three minutes after the onset breathing is not detrimental and may contribute to increase neonate vitality in puppies delivered by cesarean section.

Keywords: puppy vitality, newborn dog, cesarean section, Apgar score

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: adult, basal metabolic rate, fao/who/unu, obesity, prediction equations

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Authors: Hsiao-Lan Wang, Chun-Han Chiang, I-Chen Chen

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In Chinese Mandarin, lexical tones play an important role to provide contrasts in word meaning. They are pitch patterns and can be quantified as the fundamental frequency (F0), expressed in Hertz (Hz). In this study, we aim to investigate the influence of frequency discrimination on Chinese children’s performance of reading abilities. Fifty participants from 3rd to 4th grades, including 24 children with reading difficulties and 26 age-matched children, were examined. A serial of cognitive, language, reading and psychoacoustic tests were administrated. Magnetoencephalography (MEG) was also employed to study children’s auditory sensitivity. In the present study, auditory frequency was measured through slide-up pitch, slide-down pitch and frequency-modulated tone. The results showed that children with Chinese reading difficulties were significantly poor at phonological awareness and auditory discrimination for the identification of frequency-modulated tone. Chinese children’s character reading performance was significantly related to lexical tone awareness and auditory perception of frequency-modulated tone. In our MEG measure, we compared the mismatch negativity (MMNm), from 100 to 200 ms, in two groups. There were no significant differences between groups during the perceptual discrimination of standard sounds, fast-up and fast-down frequencies. However, the data revealed significant cluster differences between groups in the slow-up and slow-down frequencies discrimination. In the slow-up stimulus, the cluster demonstrated an upward field map at 106-151 ms (p < .001) with a strong peak time at 127ms. The source analyses of two dipole model and localization resolution model (CLARA) from 100 to 200 ms both indicated a strong source from the left temporal area with 45.845% residual variance. Similar results were found in the slow-down stimulus with a larger upward current at 110-142 ms (p < 0.05) and a peak time at 117 ms in the left temporal area (47.857% residual variance). In short, we found a significant group difference in the MMNm while children processed frequency-modulated tones with slow temporal changes. The findings may imply that perception of sound frequency signals with slower temporal modulations was related to reading and language development in Chinese. Our study may also support the recent hypothesis of underlying non-verbal auditory temporal deficits accounting for the difficulties in literacy development seen developmental dyslexia.

Keywords: Chinese Mandarin, frequency modulation sweeps, magnetoencephalography, mismatch negativity, reading difficulties

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Yusri Yusof, Chen Wong Keong

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This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

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Authors: Sung-Uk Wee, Chang-Sung Seok, Jae-Mean Koo, Jeong-Min Lee

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Gas turbine blade is important part of power plant, so it is necessary to evaluate gas turbine reliability. For better heat efficiency, inlet temperature of gas turbine has been elevated more and more so gas turbine blade is exposed to high-temperature environment. Then, higher inlet temperature affects mechanical behavior of the gas turbine blade, so it is necessary that evaluation of mechanical property of gas turbine blade at high-temperature environment. In this study, tensile test and fatigue test were performed at various high temperature, and fatigue life was predicted by Coffin-Manson equation at each temperature. The experimental results showed that gas turbine blade has a lower elastic modulus and shorter fatigue life at higher temperature.

Keywords: gas turbine blade, tensile test, fatigue life, stress-strain

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Authors: L. Laurs, A. Blazeviciene, D. Milonas

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Introduction: Nursing as a profession is grounded in moral obligation. Nursing practice is grounded in ethical standards: to not harm, to promote justice, to be accountable, and to provide safe and competent care. The nature of the nurse-patient therapeutic relationship requires acting on the patient's behalf. Moral distress consists of negative stress symptoms that occur in situations that involve ethical situations that the nurse perceives as discordant with their professional values. Aim of the Study: The purpose of this study was to assess links between moral distress of registered nurses and factors related to patient care at the end of their life. Methods and Sample: A descriptive, cross-sectional, correlational design was applied in this study. Registered nurses were recruited from seven municipal multi-profile hospitals providing both general and specialized healthcare services in Lithuania (N=1055). Research instruments included two questionnaires: Obstacles and Facilitating at the End of Life Care and Moral Distress Scale (revised). Results: Spearman’s correlation analysis was performed to assess the relationship between nurses' attitudes towards patient care at the end of life and the experienced moral distress. A statistically significant correlation between moral distress and the following factors related to patient end-of-life care has been identified: conversations with physicians on patient end-of-life problems have a positive impact on job satisfaction; some patients may be excluded from decisions about their treatment and nursing because they are questioned about their ability to assess the situation. These situations increased moral distress. Patient consciousness should not be permanently suppressed by calming medications, and the patient should be provided with all nursing care services and moral distress. Conclusions: The moral distress of nurses is significantly related to the end-of-life care of patients and their determinants: moral distress increased due to lack of discussion with doctors about problem-solving and exclusion of patients from decision-making. And it diminished by refusing calming medications to permanently suppress a patient's consciousness and providing good care for patients.

Keywords: moral distress, registered nurses, end of life, care

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Authors: Bridgette Merriman, Wen Fan

Abstract:

Background: Existing cancer survivorship literature explores varying physical, psychosocial, and psychological late effects experienced by survivors of childhood cancer. However, adolescent and young adult (AYA) survivors of childhood cancer are understudied compared to their adult and pediatric cancer counterparts. Furthermore, existing quality of life (QoL) research fails to account for how cancer survivorship affects survivors across the lifespan. Given that prior research suggests positive cognitive appraisals of adverse events - such as cancer - mitigate detrimental psychosocial symptomologies later in life; it is crucial to understand cancer’s impacts on AYA survivors of childhood malignancies across the life course in order to best support these individuals and prevent maladaptive psychosocial outcomes. Methods: This qualitative study adopted the life-course perspective to investigate the experiences of AYA survivors of childhood malignancies. Eligible patients included AYA 21-30 years old who were diagnosed with cancer <18 years old and off active treatment for >2 years. Participants were recruited through social media posts. Study fulfillment included taking part in one semi-structured video interview to explore areas of survivorship previously identified as being specific to AYA survivors. Interviews were transcribed, coded, and analyzed in accordance with narrative analysis and life-course theory. This study was approved by the Boston College Institutional Review Board. Results: Of 28 individuals who met inclusion criteria and expressed interest in the study, nineteen participants (12 women, 7 men, mean age 25.4 years old) completed the study. Life course theory analysis revealed that events relating to childhood cancer are interconnected throughout the life course rather than isolated events. This “trail of survivorship” includes age at diagnosis, transitioning to life after cancer, and relationships with other childhood survivors. Despite variability in objective characteristics surrounding these events, participants recalled positive experiences regarding at least one checkpoint, ultimately finding positive meaning from their cancer experience. Conclusions: These findings suggest that favorable subjective experiences at these checkpoints are critical in fostering positive conceptions of childhood malignancy for AYA survivors of childhood cancer. Ultimately, healthcare professionals and communities may use these findings to guide support resources and interventions for childhood cancer patients and AYA survivors, therein minimizing detrimental psychosocial effects and maximizing resiliency.

Keywords: medical sociology, pediatric oncology, survivorship, qualitative, life course perspective

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Authors: Nouioua Wafa

Abstract:

It is broadly accepted that the existence of postmodern individuals is distinguished by a predominant presence of skepticism, anxiety and loneliness. This social unrest is the consequence of a drastic shift in how reality and meaning are conceived, which has been replaced by something that is referred to in media theory and criticism as hyperreality. The purpose of this paper is to investigate the hyperreality that exists in the postmodern nihilistic American community that Don Delillo depicts in Zero K (2016) through the use of Jean Baudrillard's notions of Simulacra and Simulations. It is a troubled technological late capitalist society obsessed with immortality and fear of demise, and ergo it is an appropriate reading to implement Sigmund Freud’s theory of life drive (Eros), which refers to the life instinct fundamental to all humans and the urge to support productivity and construction. The results obtained from a qualitative analysis of Zero K indicate the presence of a clash between the character’s life drive and fear of mortality. In an effort to escape loneliness and death, the character Ross Lockhart undergoes, after a moment of hesitation, cryonic freezing in the convergence to preserve his life as well as that of his wife Artis, yet his son Jeffery is firmly convinced of the uselessness of combating the inevitable death.

Keywords: Don DeLillo, Eros, postmodernism Nihilism, Zero K

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Authors: Fatemeh Sadat Sharifi

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In this research, a barotropic model was employed to consider the tidal studies in the Persian Gulf and Oman Sea, where the only sufficient force was the tidal force. To do that, a finite-difference, free-surface model called Regional Ocean Modeling System (ROMS), was employed on the data over the Persian Gulf and Oman Sea. To analyze flow patterns of the region, the results of limited size model of The Finite Volume Community Ocean Model (FVCOM) were appropriated. The two points were determined since both are one of the most critical water body in case of the economy, biology, fishery, Shipping, navigation, and petroleum extraction. The OSU Tidal Prediction Software (OTPS) tide and observation data validated the modeled result. Next, tidal elevation and speed, and tidal analysis were interpreted. Preliminary results determine a significant accuracy in the tidal height compared with observation and OTPS data, declaring that tidal currents are highest in Hormuz Strait and the narrow and shallow region between Iranian coasts and Islands. Furthermore, tidal analysis clarifies that the M_2 component has the most significant value. Finally, the Persian Gulf tidal currents are divided into two branches: the first branch converts from south to Qatar and via United Arab Emirate rotates to Hormuz Strait. The secondary branch, in north and west, extends up to the highest point in the Persian Gulf and in the head of Gulf turns counterclockwise.

Keywords: numerical model, barotropic tide, tidal currents, OSU tidal prediction software, OTPS

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Authors: Ana B. Carrera-Aguilar , Rodrigo T. Sepulveda-Hirose, Diego A. Bernal-Gurrusquieta, Francisco A. Ramirez Casas

Abstract:

In recent years, Mexico City has presented high levels of atmospheric pollution; the city is also an example of inequality and poverty that impact metropolitan areas around the world. This combination of social and economic exclusion, coupled with high levels of pollution evidence the loss of well-being among the population. The effect of air pollution on quality of life is an area of study that has been overlooked. The purpose of this study is to find relations between air quality and quality of life in Mexico City through statistical analysis of a regression model and principal component analysis of several atmospheric contaminants (CO, NO₂, ozone, particulate matter, SO₂) and well-being indexes (HDI, poverty, inequality, life expectancy and health care index). The data correspond to official information (INEGI, SEDEMA, and CEPAL) for 2000-2018. Preliminary results show that the Human Development Index (HDI) is affected by the impacts of pollution, and its indicators are reduced in the presence of contaminants. It is necessary to promote a strong interest in this issue in Mexico City. Otherwise, the problem will not only remain but will worsen affecting those who have less and the population well-being in a generalized way.

Keywords: air quality, Mexico City, quality of life, statistics

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Authors: Wafa Nouioua

Abstract:

It is broadly accepted that the existence of postmodern individuals is distinguished by a predominant presence of skepticism, anxiety and loneliness. This social unrest is the consequence of a drastic shift in how reality and meaning are conceived, which has been replaced by something that is referred to in media theory and criticism as hyperreality. The purpose of this paper is to investigate the hyperreality that exists in the postmodern nihilistic American community that Don Delillo depicts in Zero K (2016) through the use of Jean Baudrillard notions of Simulacra and Simulations. It is a troubled technological late capitalist society obsessed with immortality and fear of demise, ergo it is an appropriate reading to implement Sigmund Freud’s theory of life drive (Eros), which refers to the life instinct fundamental to all humans and the urge to support productivity and construction. The results obtained from a qualitative analysis of Zero K indicate the presence of a clash between the character’s life drive and fear of mortality. In an effort to escape loneliness and death, the character Ross Lockhart undergoes, after a moment of hesitation, cryonic freezing in the convergence to preserve his life as well as that of his wife Artis, yet his son Jeffery is firmly convinced of the uselessness of combating the inevitable death.

Keywords: Don Dellilo, Eros, Postmodernism Nihilism, Zero K

Procedia PDF Downloads 66