Search results for: early warning model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19267

Search results for: early warning model

18907 A Cohort Study of Early Cardiologist Consultation by Telemedicine on the Critical Non-STEMI Inpatients

Authors: Wisit Wichitkosoom

Abstract:

Objectives: To find out the more effect of early cardiologist consultation using a simple technology on the diagnosis and early proper management of patients with Non-STEMI at emergency department of district hospitals without cardiologist on site before transferred. Methods: A cohort study was performed in Udonthani general hospital at Udonthani province. From 1 October 2012–30 September 2013 with 892 patients diagnosed with Non-STEMI. All patients mean aged 46.8 years of age who had been transferred because of Non-STEMI diagnosed, over a 12 week period of studied. Patients whose transferred, in addition to receiving proper care, were offered a cardiologist consultation with average time to Udonthani hospital 1.5 hour. The main outcome measure was length of hospital stay, mortality at 3 months, inpatient investigation, and transfer rate to the higher facilitated hospital were also studied. Results: Hospital stay was significantly shorter for those didn’t consult cardiologist (hazard ratio 1.19; approximate 95% CI 1.001 to 1.251; p = 0.039). The 136 cases were transferred to higher facilitated hospital. No statistically significant in overall mortality between the groups (p=0.068). Conclusions: Early cardiologist consultant can reduce length of hospital stay for patients with cardiovascular conditions outside of cardiac center. The new basic technology can apply for the safety patient.

Keywords: critical, telemedicine, safety, non STEMI

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18906 Priority Analysis for Korean Disaster Mental Health Service Model Using Analytic Hierarchy Process

Authors: Myung-Soo Lee, Sun-Jin Jo, Kyoung-Sae Na, Joo-Eon Park

Abstract:

Early intervention after a disaster is important for recovery of disaster victims and each country has its own professional mental health service system such as Disaster Psychiatric Assistant Team in Japan and Crisis Counseling Program in the USA. The purpose of this study was to determine key prior components of the Korean Disaster Psychiatric Assistant Team (K-DPAT) for building up Korean disaster mental health service system. We conducted an Analytic Hierarchy Process(AHP) with disaster mental health experts using pairwise comparison questionnaire which compares the relative importance of the key components of Korean disaster mental health service system. Forty-one experts answered the first online survey, and among them, 36 responded to the second. Ten experts were participated in panel meeting and discussed the results of the survey and AHP process. Participants decided the relative importance of the Korean disaster mental health service system regarding initial professional intervention as follows. K-DPAT could be organized at a national level (43.0%) or regional level (40.0%). K-DPAT members should be managed (59.0%) and educated (52.1%) by national level than regional or local level. K-DPAT should be organized independent of the preexisting mental health system (70.1%). Funding for K-DPAT should be from the Ministry of Public Safety and the system could be managed by Ministry of Health (65.8%). Experts agreed K-DPAT leader is suitable for key decision maker for most types of disaster except infectious disease. We expect new model for disaster mental health services can improve insufficiency of the system such as fragmentation and decrease the unmet needs of early professional intervention for the disaster victims.

Keywords: analytic hierarchy process, decision making, disaster, DPAT, mental health services

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18905 Applying Art Integration on Teaching Quality Assurance for Early Childhood Art Education

Authors: Shih Meng-Chi, Nai-Chia Chao

Abstract:

The study constructed an arts integrative curriculum for early childhood educators and kindergarten teachers to the exciting possibilities of the use of the art integration method. The art integrative curriculum applied art integration that combines and integrates various elements of music, observation, sound, art, instruments, and creation. The program consists of college courses that combine the use of technology with children’s literature, multimedia, music, dance, and drama presentation. This educational program is being used in kindergartens during the pre-service kindergarten teacher training. The study found that arts integrated curriculum was benefit for connecting across domains, multi-sensory experiences, teaching skills, implementation and creation on children art education. The art Integrating instruction helped to provide students with an understanding of the whole framework and improve the teaching quality.

Keywords: art integration, teaching quality assurance, early childhood education, arts integrated curriculum

Procedia PDF Downloads 566
18904 HRV Analysis Based Arrhythmic Beat Detection Using kNN Classifier

Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

Abstract:

Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

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18903 Early Recognition and Grading of Cataract Using a Combined Log Gabor/Discrete Wavelet Transform with ANN and SVM

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

Abstract:

Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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18902 Fast Aerodynamic Evaluation of Transport Aircraft in Early Phases

Authors: Xavier Bertrand, Alexandre Cayrel

Abstract:

The early phase of an aircraft development is instrumental as it really drives the potential of a new concept. Any weakness in the high-level design (wing planform, moveable surfaces layout etc.) will be extremely difficult and expensive to recover later in the aircraft development process. Aerodynamic evaluation in this very early development phase is driven by two main criteria: a short lead-time to allow quick iterations of the geometrical design, and a high quality of the calculations to get an accurate & reliable assessment of the current status. These two criteria are usually quite contradictory. Actually, short lead time of a couple of hours from end-to-end can be obtained with very simple tools (semi-empirical methods for instance) although their accuracy is limited, whereas higher quality calculations require heavier/more complex tools, which obviously need more complex inputs as well, and a significantly longer lead time. At this point, the choice has to be done between accuracy and lead-time. A brand new approach has been developed within Airbus, aiming at obtaining quickly high quality evaluations of the aerodynamic of an aircraft. This methodology is based on a joint use of Surrogate Modelling and a lifting line code. The Surrogate Modelling is used to get the wing sections characteristics (e.g. lift coefficient vs. angle of attack), whatever the airfoil geometry, the status of the moveable surfaces (aileron/spoilers) or the high-lift devices deployment. From these characteristics, the lifting line code is used to get the 3D effects on the wing whatever the flow conditions (low/high Mach numbers etc.). This methodology has been applied successfully to a concept of medium range aircraft.

Keywords: aerodynamics, lifting line, surrogate model, CFD

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18901 Unveiling Game Designers’ Designing Practices: Five-Essential-Steps Model

Authors: Mifrah Ahmad

Abstract:

Game designing processes vary with the intentions of the game. Digital games have versatile starting and finishing processes and these have been reported throughout the literature over decades. However, the need to understand how game designers’ practice in designing games is approached in the industry and how do they approach designing games is yet to be informed and whether they consider existing models or frameworks in their practice to assist their designing process of games. Therefore, this paper discusses 17 game designers’ participants' perspectives on how they approach designing games and how their experience of designing various games influences their practice. This research is conducted in an Australian context, through a phenomenology approach, where semi-structured interviews were designed and grounded by theory of experience by John Dewey. The audio data collected was analyzed using NVivo and interpreted using the interpretivism paradigm to contextualize the essence of game designers’ experiences in their practice and unfold their designing, developing, and iterative methodologies. As a result, a generic game-designing model is proposed that illuminates a sequence of steps that enables game designers’ initiatives toward a successful game design process. A ‘Five-Essential-Steps’ model (5ESM) for designing digital games may potentially assist early career game designers, gaming researchers as well as academics pursuing the designing process of games, educational games, or serious games.

Keywords: game designers practice, experiential design, designing models, game design approaches, designing process, software design, top-down model

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18900 Broadening the Roles of Masjid: Reviving Prophetic Holistic Model in Fostering Islamic Education and Arabic Language in South-Western Nigeria

Authors: Ahmad Tijani Surajudeen, Muhammad Zahiri Awang Mat, Aliy Abdulwahid Adebisi

Abstract:

With arrival of Islam in the South-Western Nigeria in the late fifteenth and early sixteenth centuries, various masājid established in different parts of the area played vital roles towards the betterment and unity of the Muslims. However, despite the fact that the masājid in the South-Western part of Nigeria contributed immensely to the spiritual and educational enhancement of the Muslims, it has not fully captured the holistic educational roles as a unique model used by the Prophet (S.A.W). Therefore, the primary objective of this paper is to investigate and broaden the roles of masjid towards its compartmentalized and holistic contributions among the Muslims in the south-western Nigeria. The findings from the paper have identified five holistic roles of masjid, namely, spiritual, intellectual, physical, social and emotional contributions which have been exemplified in the prophetic model of masjid. The paper has argued that the five factors must be unreservedly unified towards the betterment of the Muslims and enhancement of Islamic education and Arabic Language in the South-Western Nigeria. However, the challenges of masjid management in the South-Western Nigeria are the main hindrance in achieving the holistic roles of masjid. It is thereby suggested that, the management of masjid should take the identified prophetic model of masjid into account in order to positively improve the affairs of Muslims as well as promoting the teaching and learning of Islamic education and Arabic language among the Muslims in the South-Western Nigeria.

Keywords: worship, Islamic education, Arabic language, prophetic holistic model

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18899 Model Driven Architecture Methodologies: A Review

Authors: Arslan Murtaza

Abstract:

Model Driven Architecture (MDA) is technique presented by OMG (Object Management Group) for software development in which different models are proposed and converted them into code. The main plan is to identify task by using PIM (Platform Independent Model) and transform it into PSM (Platform Specific Model) and then converted into code. In this review paper describes some challenges and issues that are faced in MDA, type and transformation of models (e.g. CIM, PIM and PSM), and evaluation of MDA-based methodologies.

Keywords: OMG, model driven rrchitecture (MDA), computation independent model (CIM), platform independent model (PIM), platform specific model(PSM), MDA-based methodologies

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18898 Finite Element and Experimental Investigation of Ductile Crack Growth of Surface Cracks

Authors: Osama A. Terfas, Abdelhakim A. Hameda, Abdusalam A. Alktiwi

Abstract:

An investigation on ductile crack growth of shallow semi-elliptical surface cracks with a/w=0.2, a/c=0.33 under bending was carried out, where a is the crack depth, w is the plate thickness and c is the crack length at surface. Finite element analysis and experiments were modelling and the crack growth model were verified with experimental data. The results showed that the initial crack shape was no longer maintained as the crack developed under ductile tearing. The maximum growth at the deepest point at early stages was stopped when the crack depth reached half thickness and growth occurred beneath surface. Excellent agreement in the crack shape patterns was observed between the experiments and the crack growth model.

Keywords: crack growth, ductile tearing, mean stress, surface cracks

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18897 Development of a Decision-Making Method by Using Machine Learning Algorithms in the Early Stage of School Building Design

Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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18896 Levels of Family Empowerment and Parenting Skills of Parents with Children with Developmental Disabilities Who Are Users of Early Intervention Services

Authors: S. Bagur, S. Verger, B. Mut

Abstract:

Early childhood intervention (ECI) is understood as the set of interventions aimed at the child population with developmental disorders or disabilities from 0 to 6 years of age, the family, and the environment. Under the principles of family-centred practices, the members of the family nucleus are direct agents of intervention. Thus, the multidisciplinary team of professionals should work to improve family empowerment and the level of parenting skills. The aim of the present study is to analyse descriptively and differentially the level of parenting skills and family empowerment of parents using ECI services during the foster care phase. There were 135 families participating in the study. Three questionnaires were completed. The results show that the employment situation, the age of the child receiving an intervention, and the number of children in the family nucleus or the professional carrying out the intervention are variables that have a differential impact on different items of empowerment and parenting skills. The results are discussed and future lines of research are proposed, with the understanding that the initial analysis of the variables of empowerment and parenting skills may be predictors for the improvement of child development and family well-being. In addition, it is proposed to identify and analyse professional training in order to be able to adapt early care practices without depending on the discipline of the professional of reference.

Keywords: developmental disabilities, early childhood intervention, family empowerment, parenting skills

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18895 Assessment of a Rapid Detection Sensor of Faecal Pollution in Freshwater

Authors: Ciprian Briciu-Burghina, Brendan Heery, Dermot Brabazon, Fiona Regan

Abstract:

Good quality bathing water is a highly desirable natural resource which can provide major economic, social, and environmental benefits. Both in Ireland and Europe, such water bodies are managed under the European Directive for the management of bathing water quality (BWD). The BWD aims mainly: (i) to improve health protection for bathers by introducing stricter standards for faecal pollution assessment (E. coli, enterococci), (ii) to establish a more pro-active approach to the assessment of possible pollution risks and the management of bathing waters, and (iii) to increase public involvement and dissemination of information to the general public. Standard methods for E. coli and enterococci quantification rely on cultivation of the target organism which requires long incubation periods (from 18h to a few days). This is not ideal when immediate action is required for risk mitigation. Municipalities that oversee the bathing water quality and deploy appropriate signage have to wait for laboratory results. During this time, bathers can be exposed to pollution events and health risks. Although forecasting tools exist, they are site specific and as consequence extensive historical data is required to be effective. Another approach for early detection of faecal pollution is the use of marker enzymes. β-glucuronidase (GUS) is a widely accepted biomarker for E. coli detection in microbiological water quality control. GUS assay is particularly attractive as they are rapid, less than 4 h, easy to perform and they do not require specialised training. A method for on-site detection of GUS from environmental samples in less than 75 min was previously demonstrated. In this study, the capability of ColiSense as an early warning system for faecal pollution in freshwater is assessed. The system successfully detected GUS activity in all of the 45 freshwater samples tested. GUS activity was found to correlate linearly with E. coli (r2=0.53, N=45, p < 0.001) and enterococci (r2=0.66, N=45, p < 0.001) Although GUS is a marker for E. coli, a better correlation was obtained for enterococci. For this study water samples were collected from 5 rivers in the Dublin area over 1 month. This suggests a high diversity of pollution sources (agricultural, industrial, etc) as well as point and diffuse pollution sources were captured in the sample size. Such variety in the source of E. coli can account for different GUS activities/culturable cell and different ratios of viable but not culturable to viable culturable bacteria. A previously developed protocol for the recovery and detection of E. coli was coupled with a miniaturised fluorometer (ColiSense) and the system was assessed for the rapid detection FIB in freshwater samples. Further work will be carried out to evaluate the system’s performance on seawater samples.

Keywords: faecal pollution, β-glucuronidase (GUS), bathing water, E. coli

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18894 Nurse’s Role in Early Detection of Breast Cancer through Mammography and Genetic Screening and Its Impact on Patient's Outcome

Authors: Salwa Hagag Abdelaziz, Dorria Salem, Hoda Zaki, Suzan Atteya

Abstract:

Early detection of breast cancer saves many thousands of lives each year via application of mammography and genetic screening and many more lives could be saved if nurses are involved in breast care screening practices. So, the aim of the study was to identify nurse's role in early detection of breast cancer through mammography and genetic screening and its impact on patient's outcome. In order to achieve this aim, 400 women above 40 years, asymptomatic were recruited for mammography and genetic screening. In addition, 50 nurses and 6 technologists were involved in the study. A descriptive analytical design was used. Five tools were utilized: sociodemographic, mammographic examination and risk factors, women's before, during and after mammography, items relaying to technologists, and items related to nurses were also obtained. The study finding revealed that 3% of women detected for malignancy and 7.25% for fibroadenoma. Statistically, significant differences were found between mammography results and age, family history, genetic screening, exposure to smoke, and using contraceptive pills. Nurses have insufficient knowledge about screening tests. Based on these findings the present study recommended involvement of nurses in breast care which is very important to in force population about screening practices.

Keywords: mammography, early detection, genetic screening, breast cancer

Procedia PDF Downloads 537
18893 Intelligent Prediction of Breast Cancer Severity

Authors: Wahab Ali, Oyebade K. Oyedotun, Adnan Khashman

Abstract:

Breast cancer remains a threat to the woman’s world in view of survival rates, it early diagnosis and mortality statistics. So far, research has shown that many survivors of breast cancer cases are in the ones with early diagnosis. Breast cancer is usually categorized into stages which indicates its severity and corresponding survival rates for patients. Investigations show that the farther into the stages before diagnosis the lesser the chance of survival; hence the early diagnosis of breast cancer becomes imperative, and consequently the application of novel technologies to achieving this. Over the year, mammograms have used in the diagnosis of breast cancer, but the inconclusive deductions made from such scans lead to either false negative cases where cancer patients may be left untreated or false positive where unnecessary biopsies are carried out. This paper presents the application of artificial neural networks in the prediction of severity of breast tumour (whether benign or malignant) using mammography reports and other factors that are related to breast cancer.

Keywords: breast cancer, intelligent classification, neural networks, mammography

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18892 Bioengineering System for Prediction and Early Prenosological Diagnostics of Stomach Diseases Based on Energy Characteristics of Bioactive Points with Fuzzy Logic

Authors: Mahdi Alshamasin, Riad Al-Kasasbeh, Nikolay Korenevskiy

Abstract:

We apply mathematical models for the interaction of the internal and biologically active points of meridian structures. Amongst the diseases for which reflex diagnostics are effective are those of the stomach disease. It is shown that use of fuzzy logic decision-making yields good results for the prediction and early diagnosis of gastrointestinal tract diseases, depending on the reaction energy of biologically active points (acupuncture points). It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained by using fuzzy logic decision-making.

Keywords: acupuncture points, fuzzy logic, diagnostically important points (DIP), confidence factors, membership functions, stomach diseases

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18891 A Study of Small Business Failure: Impact of Leadership and the Leadership Process

Authors: Theresa Robinson Harris

Abstract:

Small businesses are important to the United States economy, yet the majority struggle to remain relevant and close before their fifth year. This qualitative study explored small business failure by comparing the experiences of small-business owners to understand their involvement with leadership during the early stages of the business, and the impact of this on the firms’ ability to survive. Participants’ experiences from two groups were compared to glean an understanding of the leadership process, how leadership differs between the groups, and to see what themes or constructs emerged that could help to explain the high failure rate. Leadership was perceived to be important when envisioning a path for the future and when providing a platform for employees to succeed. Those who embraced leadership as a skillset were more likely to get through the challenges of the early developmental years while those ignoring the importance of leadership were more likely to close prematurely. These findings suggest a disconnect with regards to the understanding, role, and benefits of leadership in small organizations, particularly young organizations in the early stages of development.

Keywords: leadership, small business, entrepreneurship, success, failure

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18890 Discussion on Big Data and One of Its Early Training Application

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

Abstract:

This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

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18889 The Influence of the Concentration and Temperature on the Rheological Behavior of Carbonyl-Methylcellulose

Authors: Mohamed Rabhi, Kouider Halim Benrahou

Abstract:

The rheological properties of the carbonyl-methylcellulose (CMC), of different concentrations (25000, 50000, 60000, 80000 and 100000 ppm) and different temperatures were studied. We found that the rheological behavior of all CMC solutions presents a pseudo-plastic behavior, it follows the model of Ostwald-de Waele. The objective of this work is the modeling of flow by the CMC Cross model. The Cross model gives us the variation of the viscosity according to the shear rate. This model allowed us to adjust more clearly the rheological characteristics of CMC solutions. A comparison between the Cross model and the model of Ostwald was made. Cross the model fitting parameters were determined by a numerical simulation to make an approach between the experimental curve and those given by the two models. Our study has shown that the model of Cross, describes well the flow of "CMC" for low concentrations.

Keywords: CMC, rheological modeling, Ostwald model, cross model, viscosity

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18888 The Role of Bone Marrow Fatty Acids in the Early Stage of Post-Menopausal Osteoporosis

Authors: Sizhu Wang, Cuisong Tang, Lin Zhang, Guangyu Tang

Abstract:

Objective: We aimed to detect the composition of bone marrow fatty acids early after ovariectomized (OVX) surgery and explore the potential mechanism. Methods: Thirty-two female Sprague-Dawley (SD) rats (12 weeks) were randomly divided into OVX group and Sham group (N=16/group), and received ovariectomy or sham surgery respectively. After 3 and 28 days, eight rats in each group were sacrificed to detect the composition of bone marrow fatty acids by gas chromatography–mass spectrometry (GC–MS) and evaluate the trabecular bone microarchitecture by micro-CT. Significant different fatty acids in the early stage of post-menopausal osteoporosis were selected by OPLS-DA and t test. Then selected fatty acids were further studied in the process of osteogenic differentiation through RT-PCR and Alizarin Red S staining. Results: An apparent sample clustering and group separation were observed between OVX group and sham group three days after surgery, which suggested the role of bone marrow fatty acids in the early stage of postmenopausal osteoporosis. Specifically, myristate, palmitoleate and arachidonate were found to play an important role in classification between OVX group and sham group. We further investigated the effect of palmitoleate and arachidonate on osteogenic differentiation and found that palmitoleate promoted the osteogenic differentiation of MC3T3-E1 cells while arachidonate inhibited this process. Conclusion: Profound bone marrow fatty acids changes have taken place in the early stage of post-menopausal osteoporosis. Bone marrow fatty acids may begin to affect osteogenic differentiation shortly after deficiency of estrogen.

Keywords: bone marrow fatty acids, GC-MS, osteoblast, osteoporosis, post-menopausal

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18887 3D Model of Rain-Wind Induced Vibration of Inclined Cable

Authors: Viet-Hung Truong, Seung-Eock Kim

Abstract:

Rain–wind induced vibration of inclined cable is a special aerodynamic phenomenon because it is easily influenced by many factors, especially the distribution of rivulet and wind velocity. This paper proposes a new 3D model of inclined cable, based on single degree-of-freedom model. Aerodynamic forces are firstly established and verified with the existing results from a 2D model. The 3D model of inclined cable is developed. The 3D model is then applied to assess the effects of wind velocity distribution and the continuity of rivulets on the cable. Finally, an inclined cable model with small sag is investigated.

Keywords: 3D model, rain - wind induced vibration, rivulet, analytical model

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18886 The Search for the Self in Psychotherapy: Findings from Relational Theory and Neuroanatomy

Authors: Harry G. Segal

Abstract:

The idea of the “self” has been essential ever since the early modern period in western culture, especially since the development of psychotherapy, but advances in neuroscience and cognitive theory challenge traditional notions of the self. More specifically, neuroanatomists have found no location of “the self” in the brain; instead, consciousness has been posited to be a rapid combination of perception, memory, anticipation of future events, and judgment. In this paper, a theoretical model is presented to address these neuroanatomical findings and to revise the historical understanding of “selfhood” in the practice of psychotherapy.

Keywords: the self, psychotherapy, the self and the brain

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18885 Early Formation of Adipocere in Subtropical Climate

Authors: Asit K. Sikary, O. P. Murty

Abstract:

Adipocere formation is a modification of the process of putrefaction. It consists mainly of saturated fatty acids, formed by the post-mortem hydrolysis and hydrogenation of body fats with the help of bacterial enzymes in the presence of warmth, moisture and anaerobic bacteria. In temperate climate, it takes weeks to develop while in India it starts to begin within 4-5 days. In this study, we have collected cases with adipocere formation, which were from the South Delhi region (average room temperature 27-390C) and autopsied at our centre. Details of the circumstances of the death, cause and time of death, surrounding environment and demographic profile of the deceased were taken into account. Total 16 cases were included in this study. Adipocere formation was predominantly present over cheeks, shoulder, breast, flanks, buttocks, and thighs. Out of 16, 11 cases were found in a dry atmosphere, 5 cases were brought from the water. There were 5 cases in which adipocere formation was seen in less than 2 days, and among them, in 1 case, as early as one day. This study showed that adipocere formation can be seen as early as 1 day in a hot and humid environment.

Keywords: adipocere, drowning, hanging, humid environment, strangulation, subtropical climate

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18884 Analyzing Safety Incidents using the Fatigue Risk Index Calculator as an Indicator of Fatigue within a UK Rail Franchise

Authors: Michael Scott Evans, Andrew Smith

Abstract:

The feeling of fatigue at work could potentially have devastating consequences. The aim of this study was to investigate whether the well-established objective indicator of fatigue – the Fatigue Risk Index (FRI) calculator used by the rail industry is an effective indicator to the number of safety incidents, in which fatigue could have been a contributing factor. The study received ethics approval from Cardiff University’s Ethics Committee (EC.16.06.14.4547). A total of 901 safety incidents were recorded from a single British rail franchise between 1st June 2010 – 31st December 2016, into the Safety Management Information System (SMIS). The safety incident types identified that fatigue could have been a contributing factor were: Signal Passed at Danger (SPAD), Train Protection & Warning System (TPWS) activation, Automatic Warning System (AWS) slow to cancel, failed to call, and station overrun. From the 901 recorded safety incidents, the scheduling system CrewPlan was used to extract the Fatigue Index (FI) score and Risk Index (RI) score of all train drivers on the day of the safety incident. Only the working rosters of 64.2% (N = 578) (550 men and 28 female) ranging in age from 24 – 65 years old (M = 47.13, SD = 7.30) were accessible for analyses. Analysis from all 578 train drivers who were involved in safety incidents revealed that 99.8% (N = 577) of Fatigue Index (FI) scores fell within or below the identified guideline threshold of 45 as well as 97.9% (N = 566) of Risk Index (RI) scores falling below the 1.6 threshold range. Their scores represent good practice within the rail industry. These findings seem to indicate that the current objective indicator, i.e. the FRI calculator used in this study by the British rail franchise was not an effective predictor of train driver’s FI scores and RI scores, as safety incidents in which fatigue could have been a contributing factor represented only 0.2% of FI scores and 2.1% of RI scores. Further research is needed to determine whether there are other contributing factors that could provide a better indication as to why there is such a significantly large proportion of train drivers who are involved in safety incidents, in which fatigue could have been a contributing factor have such low FI and RI scores.

Keywords: fatigue risk index calculator, objective indicator of fatigue, rail industry, safety incident

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18883 Verification of Simulated Accumulated Precipitation

Authors: Nato Kutaladze, George Mikuchadze, Giorgi Sokhadze

Abstract:

Precipitation forecasts are one of the most demanding applications in numerical weather prediction (NWP). Georgia, as the whole Caucasian region, is characterized by very complex topography. The country territory is prone to flash floods and mudflows, quantitative precipitation estimation (QPE) and quantitative precipitation forecast (QPF) at any leading time are very important for Georgia. In this study, advanced research weather forecasting model’s skill in QPF is investigated over Georgia’s territory. We have analyzed several convection parameterization and microphysical scheme combinations for different rainy episodes and heavy rainy phenomena. We estimate errors and biases in accumulated 6 h precipitation using different spatial resolution during model performance verification for 12-hour and 24-hour lead time against corresponding rain gouge observations and satellite data. Various statistical parameters have been calculated for the 8-month comparison period, and some skills of model simulation have been evaluated. Our focus is on the formation and organization of convective precipitation systems in a low-mountain region. Several problems in connection with QPF have been identified for mountain regions, which include the overestimation and underestimation of precipitation on the windward and lee side of the mountains, respectively, and a phase error in the diurnal cycle of precipitation leading to the onset of convective precipitation in model forecasts several hours too early.

Keywords: extremal dependence index, false alarm, numerical weather prediction, quantitative precipitation forecasting

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18882 A Deep Learning Approach to Calculate Cardiothoracic Ratio From Chest Radiographs

Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

Abstract:

The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

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18881 Climate Change Scenario Phenomenon in Malaysia: A Case Study in MADA Area

Authors: Shaidatul Azdawiyah Abdul Talib, Wan Mohd Razi Idris, Liew Ju Neng, Tukimat Lihan, Muhammad Zamir Abdul Rasid

Abstract:

Climate change has received great attention worldwide due to the impact of weather causing extreme events. Rainfall and temperature are crucial weather components associated with climate change. In Malaysia, increasing temperatures and changes in rainfall distribution patterns lead to drought and flood events involving agricultural areas, especially rice fields. Muda Agricultural Development Authority (MADA) is the largest rice growing area among the 10 granary areas in Malaysia and has faced floods and droughts in the past due to changing climate. Changes in rainfall and temperature patter affect rice yield. Therefore, trend analysis is important to identify changes in temperature and rainfall patterns as it gives an initial overview for further analysis. Six locations across the MADA area were selected based on the availability of meteorological station (MetMalaysia) data. Historical data (1991 to 2020) collected from MetMalaysia and future climate projection by multi-model ensemble of climate model from CMIP5 (CNRM-CM5, GFDL-CM3, MRI-CGCM3, NorESM1-M and IPSL-CM5A-LR) have been analyzed using Mann-Kendall test to detect the time series trend, together with standardized precipitation anomaly, rainfall anomaly index, precipitation concentration index and temperature anomaly. Future projection data were analyzed based on 3 different periods; early century (2020 – 2046), middle century (2047 – 2073) and late-century (2074 – 2099). Results indicate that the MADA area does encounter extremely wet and dry conditions, leading to drought and flood events in the past. The Mann-Kendall (MK) trend analysis test discovered a significant increasing trend (p < 0.05) in annual rainfall (z = 0.40; s = 15.12) and temperature (z = 0.61; s = 0.04) during the historical period. Similarly, for both RCP 4.5 and RCP 8.5 scenarios, a significant increasing trend (p < 0.05) was found for rainfall (RCP 4.5: z = 0.15; s = 2.55; RCP 8.5: z = 0.41; s = 8.05;) and temperature (RCP 4.5: z = 0.84; s = 0.02; RCP 8.5: z = 0.94; s = 0.05). Under the RCP 4.5 scenario, the average temperature is projected to increase up to 1.6 °C in early century, 2.0 °C in the middle century and 2.4 °C in the late century. In contrast, under RCP 8.5 scenario, the average temperature is projected to increase up to 1.8 °C in the early century, 3.1 °C in the middle century and 4.3 °C in late century. Drought is projected to occur in 2038 and 2043 (early century); 2052 and 2069 (middle century); and 2095, 2097 to 2099 (late century) under RCP 4.5 scenario. As for RCP 8.5 scenario, drought is projected to occur in 2021, 2031 and 2034 (early century); and 2069 (middle century). No drought is projected to occur in the late century under the RCP 8.5 scenario. Thus, this information can be used for the analysis of the impact of climate change scenarios on rice growth and yield besides other crops found in MADA area. Additionally, this study, it would be helpful for researchers and decision-makers in developing applicable adaptation and mitigation strategies to reduce the impact of climate change.

Keywords: climate projection, drought, flood, rainfall, RCP 4.5, RCP 8.5, temperature

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18880 Consumption and Diffusion Based Model of Tissue Organoid Development

Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Simakov

Abstract:

In vitro organoid cultivation requires the simultaneous provision of necessary vascularization and nutrients perfusion of cells during organoid development. However, many aspects of this problem are still unsolved. The functionality of vascular network intergrowth is limited during early stages of organoid development since a function of the vascular network initiated on final stages of in vitro organoid cultivation. Therefore, a microchannel network should be created in early stages of organoid cultivation in hydrogel matrix aimed to conduct and maintain minimally required the level of nutrients perfusion for all cells in the expanding organoid. The network configuration should be designed properly in order to exclude hypoxic and necrotic zones in expanding organoid at all stages of its cultivation. In vitro vascularization is currently the main issue within the field of tissue engineering. As perfusion and oxygen transport have direct effects on cell viability and differentiation, researchers are currently limited only to tissues of few millimeters in thickness. These limitations are imposed by mass transfer and are defined by the balance between the metabolic demand of the cellular components in the system and the size of the scaffold. Current approaches include growth factor delivery, channeled scaffolds, perfusion bioreactors, microfluidics, cell co-cultures, cell functionalization, modular assembly, and in vivo systems. These approaches may improve cell viability or generate capillary-like structures within a tissue construct. Thus, there is a fundamental disconnect between defining the metabolic needs of tissue through quantitative measurements of oxygen and nutrient diffusion and the potential ease of integration into host vasculature for future in vivo implantation. A model is proposed for growth prognosis of the organoid perfusion based on joint simulations of general nutrient diffusion, nutrient diffusion to the hydrogel matrix through the contact surfaces and microchannels walls, nutrient consumption by the cells of expanding organoid, including biomatrix contraction during tissue development, which is associated with changed consumption rate of growing organoid cells. The model allows computing effective microchannel network design giving minimally required the level of nutrients concentration in all parts of growing organoid. It can be used for preliminary planning of microchannel network design and simulations of nutrients supply rate depending on the stage of organoid development.

Keywords: 3D model, consumption model, diffusion, spheroid, tissue organoid

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18879 A Qualitative Study Identifying the Complexities of Early Childhood Professionals' Use and Production of Data

Authors: Sara Bonetti

Abstract:

The use of quantitative data to support policies and justify investments has become imperative in many fields including the field of education. However, the topic of data literacy has only marginally touched the early care and education (ECE) field. In California, within the ECE workforce, there is a group of professionals working in policy and advocacy that use quantitative data regularly and whose educational and professional experiences have been neglected by existing research. This study aimed at analyzing these experiences in accessing, using, and producing quantitative data. This study utilized semi-structured interviews to capture the differences in educational and professional backgrounds, policy contexts, and power relations. The participants were three key professionals from county-level organizations and one working at a State Department to allow for a broader perspective at systems level. The study followed Núñez’s multilevel model of intersectionality. The key in Núñez’s model is the intersection of multiple levels of analysis and influence, from the individual to the system level, and the identification of institutional power dynamics that perpetuate the marginalization of certain groups within society. In a similar manner, this study looked at the dynamic interaction of different influences at individual, organizational, and system levels that might intersect and affect ECE professionals’ experiences with quantitative data. At the individual level, an important element identified was the participants’ educational background, as it was possible to observe a relationship between that and their positionality, both with respect to working with data and also with respect to their power within an organization and at the policy table. For example, those with a background in child development were aware of how their formal education failed to train them in the skills that are necessary to work in policy and advocacy, and especially to work with quantitative data, compared to those with a background in administration and/or business. At the organizational level, the interviews showed a connection between the participants’ position within the organization and their organization’s position with respect to others and their degree of access to quantitative data. This in turn affected their sense of empowerment and agency in dealing with data, such as shaping what data is collected and available. These differences reflected on the interviewees’ perceptions and expectations for the ECE workforce. For example, one of the interviewees pointed out that many ECE professionals happen to use data out of the necessity of the moment. This lack of intentionality is a cause for, and at the same time translates into missed training opportunities. Another interviewee pointed out issues related to the professionalism of the ECE workforce by remarking the inadequacy of ECE students’ training in working with data. In conclusion, Núñez’s model helped understand the different elements that affect ECE professionals’ experiences with quantitative data. In particular, what was clear is that these professionals are not being provided with the necessary support and that we are not being intentional in creating data literacy skills for them, despite what is asked of them and their work.

Keywords: data literacy, early childhood professionals, intersectionality, quantitative data

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18878 Identifying Model to Predict Deterioration of Water Mains Using Robust Analysis

Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

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In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

Procedia PDF Downloads 707