Search results for: multivariate models.

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 140

Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

Abstract:

Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: obesity, adult, high in fat, stress, physical activity, consumption pattern

Procedia PDF Downloads 225

Authors: Yasmine Aridi, Lara Nasreddine, Maya Khalil, Arafat Tfayli, Anas Mugharbel, Farah Naja

Abstract:

Breast cancer is the most commonly diagnosed cancer site among women worldwide and the second most common cause of cancer mortality. Breast cancer rates differ vastly between geographical areas, countries, and within the same country. In Lebanon, the proportion of breast cancer to all other sites of tumor is 38.2%; these rates are still lower than those observed worldwide, but remain the highest among Arab countries. Studies and evidence based reviews show a strong association between breast cancer development and prognosis and dietary habits, specifically the Mediterranean diet (MD). As such, the aim of this study is to examine dietary patterns and adherence to the MD among a sample of 182 breast cancer female patients in Beirut, Lebanon. Subjects were recruited from two major hospitals; a private medical center and a public hospital. All subjects were administered two questionnaires: socio- demographics and Mediterranean diet adherence. Five Mediterranean scores were calculated: MS, MSDPS, PMDI, PREDIMED and DDS. The mean age of the participants was 53.78 years. The overall adherence to the Mediterranean diet (MD) was low since the sample means of 3 out of the 5 calculated scores were less than the scores’ medians. Given that 4 out of the 5 Mediterranean scores significantly varied between the recruitment sites, women in the private medical center were found to adhere more to the MD. Our results also show that the majority of the sample population’s intakes are exceeding the recommendations for total and saturated fat, while meeting the requirements for fiber, EPA, DHA and Linolenic Acid. Participants in the private medical center were consuming significantly more calories, carbohydrates, fiber, sugar, Lycopene, Calcium, Iron and Folate and less fat. After conducting multivariate linear regression analyses, the following significant results were observed: positive associations between MD (CPMDI, PREDIMED) and monthly income & current state of health, while negative associations between MD (MSDPS, PREDIMED) and age & employment status. Our findings indicated a low overall adherence to the MD and identified factors associated with it; which suggests a need to address dietary habits among BC patients in Lebanon, specifically encouraging them to adhere to their traditional Mediterranean diet.

Keywords: Adherence, Breast cancer, Dietary patterns, Mediterranean diet, Nutrition

Procedia PDF Downloads 408

Authors: Tadele Araya, Tsehaye Asmelash, Girmatsion Fiseha

Abstract:

Background: Hepatitis B virus (HBV), Hepatitis C virus (HCV) and Human Immunodeficiency Virus (HIV) constitute serious healthcare problems worldwide. Blood-borne pathogens HBV, HCV and HIV are commonly associated with infections among substance or Injection Drug Users (IDUs). The objective of this study was to determine the prevalence of HBV, HCV, and HIV infections among substance users in Mekelle Substance users Treatment and Rehabilitation Centers. Methods: A cross-sectional study design was used from Dec 2020 to Sep / 2021 to conduct the study. A total of 600 substance users were included. Data regarding the socio-demographic, clinical and sexual behaviors of the substance users were collected using a structured questionnaire. For laboratory analysis, 5-10 ml of venous blood was taken from the substance users. The laboratory analysis was performed by Enzyme-Linked Immunosorbent Assay (ELISA) at Mekelle University, Department of Medical Microbiology and Immunology Research Laboratory. The Data was analyzed using SPSS and Epi-data. The association of variables with HBV, HCV and HIV infections was determined using multivariate analysis and a P value < 0.05 was considered statistically significant. Result: The overall prevalence rate of HBV, HCV and HIV infections were 10%, 6.6%, and 7.5%, respectively. The mean age of the study participants was 28.12 ± 6.9. A higher prevalence of HBV infection was seen in participants who were users of drug injections and in those who were infected with HIV. HCV was comparatively higher in those who had a previous history of unsafe surgical procedures than their counterparts. Homeless participants were highly exposed to HCV and HIV infections than their counterparts. The HBV/HIV Co-infection prevalence was 3.5%. Those doing unprotected sexual practices [P= 0.03], Injection Drug users [P= 0.03], those who had an HBV-infected person in their family [P=0.02], infected with HIV [P= 0.025] were statistically associated with HBV infection. HCV was significantly associated with Substance users and previous history of unsafe surgical procedures [p=0.03, p=0.04), respectively. HIV was significantly associated with unprotected sexual practices and being homeless [p=0.045, p=0.05) respectively. Conclusion-The highly prevalent viral infection was HBV compared to others. There was a High prevalence of HBV/HIV co-infection. The presence of HBV-infected persons in a family, unprotected sexual practices and sharing of needles for drug injection were the risk factors associated with HBV, HIV, and HCV. Continuous health education and screening of the viral infection coupled with medical and psychological treatment is mandatory for the prevention and control of the infections.

Keywords: hepatitis b virus, hepatitis c virus, HIV, substance users

Procedia PDF Downloads 72

Authors: Md Monoarul Haque

Abstract:

Nutritional status is a sensitive indicator of community health and nutrition among preschool children, especially the prevalence of undernutrition that affects all dimensions of human development and leads to growth faltering in early life. The present study is an attempt to assess the food intake pattern and nutritional status of pre-school Chakma tribe children. It was a cross-sectional community based study. The subjects were selected purposively. This study was conducted at Savar Upazilla of Rangamati. Rangamati is located in the Chittagong Division. Anthropometric data height and weight of the study subjects were collected by standard techniques. Nutritional status was measured using Z score according WHO classification. χ2 test, independent t-test, Pearson’s correlation, multiple regression and logistic regression was performed as P<0.05 level of significance. Statistical analyses were performed by appropriate univariate and multivariate techniques using SPSS windows 11.5. Moderate (-3SD to <-2SD) to severe underweight (<-3SD) were 23.8% and 76.2% study subjects had normal weight for their age. Moderate (-3SD to <-2SD) to severe (<-3SD) stunted children were only 25.6% and 74.4% children were normal and moderate to severe wasting were 14.7% whereas normal child was 85.3%. Significant association had been found between child nutritional status and monthly family income, mother education and occupation of father and mother. Age, sex and incomes of the family, education of mother and occupation of father were significantly associated with WAZ and HAZ of the study subjects (P=0.0001, P=0.025, P=0.001 and P=0.0001, P=0.003, P=0.031, P=0.092, P=0.008). Maximum study subjects took local small fish and some traditional tribal food like bashrool, jhijhipoka and pork very much popular food among tribal children. Energy, carbohydrate and fat intake was significantly associated with HAZ, WAZ, BAZ and MUACZ. This study demonstrates that malnutrition among tribal children in Bangladesh is much better than national scenario in Bangladesh. Significant association was found between child nutritional status and family monthly income, mother education and occupation of father and mother. Most of the study subjects took local small fish and some traditional tribal food. Significant association was also found between child nutritional status and dietary intake of energy, carbohydrate and fat.

Keywords: food intake pattern, nutritional status, preschool children, Chakma ethnic community

Procedia PDF Downloads 492

Authors: Shreya Poddar

Abstract:

Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

Procedia PDF Downloads 45

Authors: Fatemeh Rouhi, Hadi Nassiri

Abstract:

Earning forecast is a key element in economic decisions but there are some situations, such as conflicts of interest in financial reporting, complexity and lack of direct access to information has led to the phenomenon of information asymmetry among individuals within the organization and external investors and creditors that appear. The adverse selection and moral hazard in the investor's decision and allows direct assessment of the difficulties associated with data by users makes. In this regard, the role of trustees in corporate governance disclosure is crystallized that includes controls and procedures to ensure the lack of movement in the interests of the company's management and move in the direction of maximizing shareholder and company value. Therefore, the earning forecast of companies in the capital market and the need to identify factors influencing this study was an attempt to make relationship between moral hazard and corporate governance with earning forecast quality companies operating in the capital market and its impact on Earnings Forecasts quality by the company to be established. Getting inspiring from the theoretical basis of research, two main hypotheses and sub-hypotheses are presented in this study, which have been examined on the basis of available models, and with the use of Panel-Data method, and at the end, the conclusion has been made at the assurance level of 95% according to the meaningfulness of the model and each independent variable. In examining the models, firstly, Chow Test was used to specify either Panel Data method should be used or Pooled method. Following that Housman Test was applied to make use of Random Effects or Fixed Effects. Findings of the study show because most of the variables are positively associated with moral hazard with earnings forecasts quality, with increasing moral hazard, earning forecast quality companies listed on the Tehran Stock Exchange is increasing. Among the variables related to corporate governance, board independence variables have a significant relationship with earnings forecast accuracy and earnings forecast bias but the relationship between board size and earnings forecast quality is not statistically significant.

Keywords: corporate governance, earning forecast quality, moral hazard, financial sciences

Procedia PDF Downloads 307

Authors: Ankit Kumar Yadav, Nagendra R. Velaga

Abstract:

Driving under the influence of alcohol impairs the driving performance and increases the crash risks worldwide. The present study investigated the effect of different Blood Alcohol Concentrations (BAC) on the accelerating and braking behaviour of drivers with the help of driving simulator experiments. Eighty-two licensed Indian drivers drove on the rural road environment designed in the driving simulator at BAC levels of 0.00%, 0.03%, 0.05%, and 0.08% respectively. Driving performance was analysed with the help of vehicle control performance indicators such as mean acceleration and mean brake pedal force of the participants. Preliminary analysis reported an increase in mean acceleration and mean brake pedal force with increasing BAC levels. Generalized linear mixed models were developed to quantify the effect of different alcohol levels and explanatory variables such as driver’s age, gender and other driver characteristic variables on the driving performance indicators. Alcohol use was reported as a significant factor affecting the accelerating and braking performance of the drivers. The acceleration model results indicated that mean acceleration of the drivers increased by 0.013 m/s², 0.026 m/s² and 0.027 m/s² for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Results of the brake pedal force model reported that mean brake pedal force of the drivers increased by 1.09 N, 1.32 N and 1.44 N for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Age was a significant factor in both the models where one year increase in drivers’ age resulted in 0.2% reduction in mean acceleration and 19% reduction in mean brake pedal force of the drivers. It shows that driving experience could compensate for the negative effects of alcohol to some extent while driving. Female drivers were found to accelerate slower and brake harder as compared to the male drivers which confirmed that female drivers are more conscious about their safety while driving. It was observed that drivers who were regular exercisers had better control on their accelerator pedal as compared to the non-regular exercisers during drunken driving. The findings of the present study revealed that drivers tend to be more aggressive and impulsive under the influence of alcohol which deteriorates their driving performance. Drunk driving state can be differentiated from sober driving state by observing the accelerating and braking behaviour of the drivers. The conclusions may provide reference in making countermeasures against drinking and driving and contribute to traffic safety.

Keywords: alcohol, acceleration, braking behaviour, driving simulator

Procedia PDF Downloads 134

Authors: Alaa Morsy, Youssef Ibrahim

Abstract:

Earthquake is one of the most catastrophic events, which makes enormous harm to properties and human lives. As a piece of a safe building configuration, reinforced concrete walls are given in structures to decrease horizontal displacements under seismic load. Shear walls are additionally used to oppose the horizontal loads that might be incited by the impact of wind. Reinforced concrete walls in residential buildings might have openings that are required for windows in outside walls or for doors in inside walls or different states of openings due to architectural purposes. The size, position, and area of openings may fluctuate from an engineering perspective. Shear walls can encounter harm around corners of entryways and windows because of advancement of stress concentration under the impact of vertical or horizontal loads. The openings cause a diminishing in shear wall capacity. It might have an unfavorable impact on the stiffness of reinforced concrete wall and on the seismic reaction of structures. Finite Element Method using software package ‘ANSYS ver. 12’ becomes an essential approach in analyzing civil engineering problems numerically. Now we can make various models with different parameters in short time by using ANSYS instead of doing it experimentally, which consumes a lot of time and money. Finite element modeling approach has been conducted to study the effect of opening shape, size and position in RC wall with different thicknesses under axial and lateral static loads. The proposed finite element approach has been verified with experimental programme conducted by the researchers and validated by their variables. A very good correlation has been observed between the model and experimental results including load capacity, failure mode, and lateral displacement. A parametric study is applied to investigate the effect of opening size, shape, position on different reinforced concrete wall thicknesses. The results may be useful for improving existing design models and to be applied in practice, as it satisfies both the architectural and the structural requirements.

Keywords: Ansys, concrete walls, openings, out of plane behavior, seismic, shear wall

Procedia PDF Downloads 153

Authors: A. Douara, N. Kermas, B. Djellouli

Abstract:

In this study, we report calculations of gate capacitance of AlGaN/GaN HEMTs with nextnano device simulation software. We have used a physical gate capacitance model for III-V FETs that incorporates quantum capacitance and centroid capacitance in the channel. These simulations explore various device structures with different values of barrier thickness and channel thickness. A detailed understanding of the impact of gate capacitance in HEMTs will allow us to determine their role in future 10 nm physical gate length node.

Keywords: gate capacitance, AlGaN/GaN, HEMTs, quantum capacitance, centroid capacitance

Procedia PDF Downloads 386

Authors: Kristin Thooft

Abstract:

— Increasing pressure to manage healthcare costs has resulted in shifting care towards ambulatory settings and is driving a focus on cost transparency. There are few nurse staffing to workload models developed for ambulatory settings, less for multi-specialty clinics. Of the existing models, few have been evaluated against outcomes to understand any impact. This evaluation took place after the AWARD model for nurse staffing to workload was implemented in a multi-specialty clinic at a regional healthcare system in the Midwest. The multi-specialty clinic houses 26 medical and surgical specialty practices. The AWARD model was implemented in two specialty practices in October 2020. Donabedian’s Structure-Process-Outcome (SPO) model was used to evaluate outcomes based on changes to the structure and processes of care provided. The AWARD model defined and quantified the processes, recommended changes in the structure of day-to-day nurse staffing. Cost of care per patient visit, total visits, a total nurse performed visits used as structural and process measures, influencing the outcomes of cost of care and access to care. Independent t-tests were used to compare the difference in variables pre-and post-implementation. The SPO model was useful as an evaluation tool, providing a simple framework that is understood by a diverse care team. No statistically significant changes in the cost of care, total visits, or nurse visits were observed, but there were differences. Cost of care increased and access to care decreased. Two weeks into the post-implementation period, the multi-specialty clinic paused all non-critical patient visits due to a second surge of the COVID-19 pandemic. Clinic nursing staff was re-allocated to support the inpatient areas. This negatively impacted the ability of the Nurse Manager to utilize the AWARD model to plan daily staffing fully. The SPO framework could be used for the ongoing assessment of nurse staffing performance. Additional variables could be measured, giving a complete picture of the impact of nurse staffing. Going forward, there must be a continued focus on the outcomes of care and the value of nursing

Keywords: ambulatory, clinic, evaluation, outcomes, staffing, staffing model, staffing to workload

Procedia PDF Downloads 165

Authors: AnjalI A. Prasad

Abstract:

Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms.

Keywords: BERT, CNN, LSTM, RNN

Procedia PDF Downloads 194

Authors: Selim M. Khan

Abstract:

Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

Procedia PDF Downloads 85

Authors: Irfan Anjum Manarvi, Fawzi Aljassir

Abstract:

Human bones have been a keen area of research over a long time in the field of biomechanical engineering. Medical professionals, as well as engineering academics and researchers, have investigated various bones by using medical, mechanical, and materials approaches to discover the available body of knowledge. Their major focus has been to establish properties of these and ultimately develop processes and tools either to prevent fracture or recover its damage. Literature shows that mechanical professionals conducted a variety of tests for hardness, deformation, and strain field measurement to arrive at their findings. However, they considered these results accuracy to be insufficient due to various limitations of tools, test equipment, difficulties in the availability of human bones. They proposed the need for further studies to first overcome inaccuracies in measurement methods, testing machines, and experimental errors and then carry out experimental or theoretical studies. Finite Element analysis is a technique which was developed for the aerospace industry due to the complexity of design and materials. But over a period of time, it has found its applications in many other industries due to accuracy and flexibility in selection of materials and types of loading that could be theoretically applied to an object under study. In the past few decades, the field of biomechanical engineering has also started to see its applicability. However, the work done in the area of Tarsals, metatarsals and phalanges using this technique is very limited. Therefore, present research has been focused on using this technique for analysis of these critical bones of the human body. This technique requires a 3-dimensional geometric computer model of the object to be analyzed. In the present research, a 3d laser scanner was used for accurate geometric scans of individual tarsals, metatarsals, and phalanges from a typical human foot to make these computer geometric models. These were then imported into a Finite Element Analysis software and a length refining process was carried out prior to analysis to ensure the computer models were true representatives of actual bone. This was followed by analysis of each bone individually. A number of constraints and load conditions were applied to observe the stress and strain distributions in these bones under the conditions of compression and tensile loads or their combination. Results were collected for deformations in various axis, and stress and strain distributions were observed to identify critical locations where fracture could occur. A comparative analysis of failure properties of all the three types of bones was carried out to establish which of these could fail earlier which is presented in this research. Results of this investigation could be used for further experimental studies by the academics and researchers, as well as industrial engineers, for development of various foot protection devices or tools for surgical operations and recovery treatment of these bones. Researchers could build up on these models to carryout analysis of a complete human foot through Finite Element analysis under various loading conditions such as walking, marching, running, and landing after a jump etc.

Keywords: tarsals, metatarsals, phalanges, 3D scanning, finite element analysis

Procedia PDF Downloads 317

Authors: Hameed Ullah, Shujaul Mulk Khan, Zahid Ullah, Zeeshan Ahmad Sadia Jahangir, Abdullah, Amin Ur Rahman, Muhammad Suliman, Dost Muhammad

Abstract:

The interrelationship between vegetation and abiotic variables inside an ecosystem is one of the main jobs of plant scientists. This study was designed to investigate the vegetation structure and species diversity along with the environmental variables in the Yakhtangay hill district Shangla of the Himalayan Mountain series Pakistan by using multivariate statistical analysis. Quadrat’s method was used and a total of 171 Quadrats were laid down 57 for Tree, Shrubs and Herbs, respectively, to analyze the phytosociological attributes of the vegetation. The vegetation of the selected area was classified into different Life and leaf-forms according to Raunkiaer classification, while PCORD software version 5 was used to classify the vegetation into different plants communities by Two-way indicator species Analysis (TWINSPAN). The CANOCCO version 4.5 was used for DCA and CCA analysis to find out variation directories of vegetation with different environmental variables. A total of 114 plants species belonging to 45 different families was investigated inside the area. The Rosaceae (12 species) was the dominant family followed by Poaceae (10 species) and then Asteraceae (7 species). Monocots were more dominant than Dicots and Angiosperms were more dominant than Gymnosperms. Among the life forms the Hemicryptophytes and Nanophanerophytes were dominant, followed by Therophytes, while among the leaf forms Microphylls were dominant, followed by Leptophylls. It is concluded that among the edaphic factors such as soil pH, the concentration of soil organic matter, Calcium Carbonates concentration in soil, soil EC, soil TDS, and physiographic factors such as Altitude and slope are affecting the structure of vegetation, species composition and species diversity at the significant level with p-value ≤0.05. The Vegetation of the selected area was classified into four major plants communities and the indicator species for each community was recorded. Classification of plants into 4 different communities based upon edaphic gradients favors the individualistic hypothesis. Indicator Species Analysis (ISA) shows the indicators of the study area are mostly indicators to the Himalayan or moist temperate ecosystem, furthermore, these indicators could be considered for micro-habitat conservation and respective ecosystem management plans.

Keywords: species richness, edaphic gradients, canonical correspondence analysis (CCA), TWCA

Procedia PDF Downloads 137

Authors: Getahun Nigusie Demise

Abstract:

Background; antiretroviral treatment reduce HIV-related morbidity, and prolonged survival of patients however, there is lack of up-to-date information concerning the treatment long term effect on the survival of HIV positive children especially in the study area. Objective: The aim of this study is to assess the incidence and predictors of mortality among HIV positive children on antiretroviral therapy (ART) in public hospitals of Harer town who were enrolled from 2011 to 2021. Methodology: Institution based retrospective cohort study was conducted among 429 HIV positive children enrolled in ART clinic from January 1st 2011 to December30th 2021. Data were collected from medical cards by using a data extraction form, Descriptive analyses were used to Summarized the results, and life table was used to estimate survival probability at specific point of time after introduction of ART. Kaplan Meier survival curve together with log rank test was used to compare survival between different categories of covariates, and Multivariate Cox-proportional hazard regression model was used to estimate adjusted Hazard rate. Variables with p-values ≤0.25 in bivariable analysis were candidates to the multivariable analysis. Finally, variables with p-values < 0.05 were considered as significant variables. Results: The study participants had followed for a total of 2549.6 child-years (30596 child months) with an overall mortality rate of 1.5 (95% CI: 1.1, 2.04) per 100 child-years. Their median survival time was 112 months (95% CI: 101–117). There were 38 children with unknown outcome, 39 deaths, and 55 children transfer out to different facility. The overall survival at 6, 12, 24, 48 months were 98%, 96%, 95%, 94% respectively. being in WHO clinical Stage four (AHR=4.55, 95% CI:1.36, 15.24), having anemia(AHR=2.56, 95% CI:1.11, 5.93), baseline low absolute CD4 count (AHR=2.95, 95% CI: 1.22, 7.12), stunting (AHR=4.1, 95% CI: 1.11, 15.42), wasting (AHR=4.93, 95% CI: 1.31, 18.76), poor adherence to treatment (AHR=3.37, 95% CI: 1.25, 9.11), having TB infection at enrollment (AHR=3.26, 95% CI: 1.25, 8.49),and no history of change their regimen(AHR=7.1, 95% CI: 2.74, 18.24), were independent predictors of death. Conclusion: more than half of death occurs within 2 years. Prevalent tuberculosis, anemia, wasting, and stunting nutritional status, socioeconomic factors, and baseline opportunistic infection were independent predictors of death. Increasing early screening and managing those predictors are required.

Keywords: human immunodeficiency virus-positive children, anti-retroviral therapy, survival, treatment, Ethiopia

Procedia PDF Downloads 26

Authors: Emmanuel Pedler, Elena Raevskikh, Maxime Jaffré

Abstract:

Can the cultural geography of European cities be durably managed by European policies? To answer this question, two hypotheses can be proposed. (1) Either European cultural policies are able to erase cultural inequalities between the territories through the creation of new areas of cultural attractiveness in each beneficiary neighborhood, city or country. Or, (2) each European region historically rooted in a number of endogenous socio-historical, political or demographic factors is not receptive to exogenous political influences. Thus, the cultural attractiveness of a territory is difficult to measure and to impact by top-down policies in the long term. How do these two logics - European and local - interact and contribute to the emergence of a valued, popular sense of a common European cultural identity? Does this constant interaction between historical backgrounds and new political concepts encourage a positive identification with the European project? The European cultural policy programs, such as ECC (European Capital of Culture), seek to develop new forms of civic cohesion through inclusive and participative cultural events. The cultural assets of a city elected ‘ECC’ are mobilized to attract a wide range of new audiences, including populations poorly integrated into local cultural life – and consequently distant from pre-existing cultural offers. In the current context of increasingly heterogeneous individual perceptions of Europe, the ECC program aims to promote cultural forms and institutions that should accelerate both territorial and cross-border European cohesion. The new cultural consumption pattern is conceived to stimulate integration and mobility, but also to create a legitimate and transnational ideal European citizen type. Our comparative research confronts contrasting cases of ‘European Capitals of Culture’ from the south and from the north of Europe, cities recently concerned by the ECC political mechanism and cities that were elected ECC in the past, multi-centered cultural models vs. highly centralized cultural models. We aim to explore the impacts of European policies on the urban cultural geography, but also to understand the current obstacles for its efficient implementation.

Keywords: urbanism, cultural policies, cultural institutions, european cultural capitals, heritage industries, exclusion effects

Procedia PDF Downloads 249

Authors: Layal Mansour

Abstract:

The aim of this paper is to identify whether oil price volatility or geopolitical risks can predict future financial stress periods or economic recessions in Kuwait. We construct the first Financial Stress Index for Kuwait (FSIK) that includes informative vulnerable indicators of the main financial sectors: the banking sector, the equities market, and the foreign exchange market. The study covers the period from 2000 to 2020, so it includes the two recent most devastating world economic crises with oil price fluctuation: the Covid-19 pandemic crisis and Ukraine-Russia War. All data are taken by the central bank of Kuwait, the World Bank, IMF, DataStream, and from Federal Reserve System St Louis. The variables are computed as the percentage growth rate, then standardized and aggregated into one index using the variance equal weights method, the most frequently used in the literature. The graphical FSIK analysis provides detailed information (by dates) to policymakers on how internal financial stability depends on internal policy and events such as government elections or resignation. It also shows how monetary authorities or internal policymakers’ decisions to relieve personal loans or increase/decrease the public budget trigger internal financial instability. The empirical analysis under vector autoregression (VAR) models shows the dynamic causal relationship between the oil price fluctuation and the Kuwaiti economy, which relies heavily on the oil price. Similarly, using vector autoregression (VAR) models to assess the impact of the global geopolitical risks on Kuwaiti financial stability, results reveal whether Kuwait is confronted with or sheltered from geopolitical risks. The Financial Stress Index serves as a guide for macroprudential regulators in order to understand the weakness of the overall Kuwaiti financial market and economy regardless of the Kuwaiti dinar strength and exchange rate stability. It helps policymakers predict future stress periods and, thus, address alternative cushions to confront future possible financial threats.

Keywords: Kuwait, financial stress index, causality test, VAR, oil price, geopolitical risks

Procedia PDF Downloads 72

Authors: Graziano Chesi

Abstract:

The topological entropy plays a key role in linear dynamical systems, allowing one to establish the existence of stabilizing feedback controllers for linear systems in the presence of communications constraints. This paper addresses the determination of a robust value of the topological entropy in nonlinear dynamical systems, specifically the largest value of the topological entropy over all linearized models in a region of interest of the state space. It is shown that a sufficient condition for establishing upper bounds of the sought robust value of the topological entropy can be given in terms of a semidefinite program (SDP), which belongs to the class of convex optimization problems.

Keywords: non-linear system, communication constraint, topological entropy

Procedia PDF Downloads 310

Authors: O. Ekrami, P. Claes, S. Van Dongen

Abstract:

Fluctuating asymmetry (FA) has been studied for many years as an indicator of developmental stability or ‘genetic quality’ based on the assumption that perfect symmetry is ideally the expected outcome for a bilateral organism. Further studies have also investigated the possible link between FA and attractiveness or levels of masculinity or femininity. These hypotheses have been mostly examined using 2D images, and the structure of interest is usually presented using a limited number of landmarks. Such methods have the downside of simplifying and reducing the dimensionality of the structure, which will in return increase the error of the analysis. In an attempt to reach more conclusive and accurate results, in this study we have used high-resolution 3D scans of human faces and have developed an algorithm to measure and localize FA, taking a spatially-dense approach. A symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to examine the precision of our mapping step. The protocol’s accuracy in measurement and localizing FA is assessed using simulated faces with known amounts of asymmetry added to them. The results of validation of our approach show that the algorithm is perfectly capable of locating and measuring FA in 3D simulated faces. With the use of such algorithm, the additional captured information on asymmetry can be used to improve the studies of FA as an indicator of fitness or attractiveness. This algorithm can especially be of great benefit in studies of high number of subjects due to its automated and time-efficient nature. Additionally, taking a spatially dense approach provides us with information about the locality of FA, which is impossible to obtain using conventional methods. It also enables us to analyze the asymmetry of a morphological structures in a multivariate manner; This can be achieved by using methods such as Principal Components Analysis (PCA) or Factor Analysis, which can be a step towards understanding the underlying processes of asymmetry. This method can also be used in combination with genome wide association studies to help unravel the genetic bases of FA. To conclude, we introduced an algorithm to study and analyze asymmetry in human faces, with the possibility of extending the application to other morphological structures, in an automated, accurate and multi-variate framework.

Keywords: developmental stability, fluctuating asymmetry, morphometrics, 3D image processing

Procedia PDF Downloads 129

Authors: Simon B.A. Egli, Katja Rost

Abstract:

Literature on redistributive preferences has proliferated in past decades. A core assumption behind it is that variation in redistributive preferences can explain different levels of redistribution. In contrast, this paper considers the reverse. What if it is redistribution that changes redistributive preferences? The core assumption behind the argument is that if self-interest - which we label concrete preferences - and ideology - which we label abstract preferences - come into conflict, the former will prevail and lead to an adjustment of the latter. To test the hypothesis, data from a survey conducted in Switzerland during the first wave of the COVID-19 crisis is used. A significant portion of the workforce at the time unexpectedly received state money through the short-time working program. Short-time work was used as a proxy for self-interest and was tested (1) on the support given to hypothetical, ailing firms during the crisis and (2) on the prioritization of justice principles guiding state action. In a first step, several models using OLS-regressions on political orientation were estimated to test our hypothesis as well as to check for non-linear effects. We expected support for ailing firms to be the same regardless of ideology but only for people on short-time work. The results both confirm our hypothesis and suggest a non-linear effect. Far-right individuals on short-time work were disproportionally supportive compared to moderate ones. In a second step, ordered logit models were estimated to test the impact of short-time work and political orientation on the rankings of the distributive justice principles need, performance, entitlement, and equality. The results show that being on short-time work significantly alters the prioritization of justice principles. Right-wing individuals are much more likely to prioritize need and equality over performance and entitlement when they receive government assistance. No such effect is found among left-wing individuals. In conclusion, we provide moderate to strong evidence that unexpectedly finding oneself at the receiving end changes redistributive preferences if personal ideology is antithetical to redistribution. The implications of our findings on the study of populism, personal ideologies, and political change are discussed.

Keywords: COVID-19, ideology, redistribution, redistributive preferences, self-interest

Procedia PDF Downloads 132

Authors: Oloruntegbe Kunle Oke, Alake Ese Monica, Odutuyi Olubu Musili

Abstract:

This research explores the differing effectiveness of cascade and cluster models in professional development programs for educators in Ondo State, Nigeria. The cascade model emphasizes a top-down approach, where training is cascaded from expert trainers to lower levels of teachers. In contrast, the cluster model, a bottom-up approach, fosters collaborative learning among teachers within specific clusters. Through a review of the literature and empirical studies of the implementations of the former in two academic sessions followed by the cluster model in another two, the study examined their effectiveness on teacher development, productivity and students’ achievements. The study also drew a comparative analysis of the strengths and weaknesses associated with each model, considering factors such as scalability, cost-effectiveness, adaptability in various contexts, and sustainability. 2500 teachers from Ondo State Primary Schools participated in the cascade with intensive training in five zones for a week each in two academic sessions. On the other hand, 1,980 and 1,663 teachers in 52 and 34 clusters, respectively, were in the first and the following session. The programs were designed for one week of rigorous training of teachers by facilitators in the former while the latter was made up of four components: sit-in-observation, need-based assessment workshop, pre-cluster and the actual cluster meetings in addition to sensitization, and took place one day a week for ten weeks. Validated Cluster Impact Survey Instruments, CISI and Teacher’s Assessment Questionnaire (TAQ) were administered to ascertain the effectiveness of the models during and after implementation. The findings from the literature detailed specific effectiveness, strengths and limitations of each approach, especially the potential for inconsistencies and resistance to change. Findings from the data collected revealed the superiority of the cluster model. Response to TAQ equally showed content knowledge and skill update in both but were more sustained in the cluster model. Overall, the study contributes to the ongoing discourse on effective strategies for improving teacher training and enhancing student outcomes, offering practical recommendations for the development and implementation of future professional development projects.

Keywords: cascade model, cluster model, teachers’ development, productivity, students’ achievement

Procedia PDF Downloads 21

Authors: Marybec Griffin

Abstract:

Purpose: The purpose of this cross-sectional study was to get a better understanding of healthcare usage and satisfaction among young adult gay men (YAGM), including the facility used as the usual source of healthcare, preference for coordinated healthcare, and if their primary care provider (PCP) adequately addressed the health needs of gay men. Methods: Interviews were conducted among n=800 YAGM in New York City (NYC). Participants were surveyed about their sociodemographic characteristics and healthcare usage and satisfaction access using multivariable logistic regression models. The surveys were conducted between November 2015 and June 2016. Results: The mean age of the sample was 24.22 years old (SD=4.26). The racial and ethnic background of the participants is as follows: 35.8% (n=286) Black Non-Hispanic, 31.9% (n=225) Hispanic/Latino, 20.5% (n=164) White Non-Hispanic, 4.4% (n=35) Asian/Pacific Islander, and 6.9% (n=55) reporting some other racial or ethnic background. 31.1% (n=249) of the sample had an income below $14,999. 86.7% (n=694) report having either public or private health insurance. For usual source of healthcare, 44.6% (n=357) of the sample reported a private doctor’s office, 16.3% (n=130) reported a community health center, and 7.4% (n=59) reported an urgent care facility, and 7.6% (n=61) reported not having a usual source of healthcare. 56.4% (n=451) of the sample indicated a preference for coordinated healthcare. 54% (n=334) of the sample were very satisfied with their healthcare. Findings from multivariable logistical regression models indicate that participants with higher incomes (AOR=0.54, 95% CI 0.36-0.81, p < 0.01) and participants with a PCP (AOR=0.12, 95% CI 0.07-0.20, p < 0.001) were less likely to use a walk-in facility as their usual source of healthcare. Results from the second multivariable logistic regression model indicated that participants who experienced discrimination in a healthcare setting were less likely to prefer coordinated healthcare (AOR=0.63, 95% CI 0.42-0.96, p < 0.05). In the final multivariable logistic model, results indicated that participants who had disclosed their sexual orientation to their PCP (AOR=2.57, 95% CI 1.25-5.21, p < 0.01) and were comfortable discussing their sexual activity with their PCP (AOR=8.04, 95% CI 4.76-13.58, p < 0.001) were more likely to agree that their PCP adequately addressed the healthcare needs of gay men. Conclusion: Understanding healthcare usage and satisfaction among YAGM is necessary as the healthcare landscape changes, especially given the relatively recent addition of urgent care facilities. The type of healthcare facility used as a usual source of care influences the ability to seek comprehensive and coordinated healthcare services. While coordinated primary and sexual healthcare may be ideal, individual preference for this coordination among YAGM is desired but may be limited due to experiences of discrimination in primary care settings.

Keywords: healthcare policy, gay men, healthcare access, Affordable Care Act

Procedia PDF Downloads 221

Authors: Magdalena Smoktunowicz, Renata Wawrzyniak, Malgorzata Waleron, Krzysztof Waleron

Abstract:

Pectobacterium spp. were previously classified into the Erwinia genus founded in 1917 to unite at that time all Gram-negative, fermentative, nonsporulating and peritrichous flagellated plant pathogenic bacteria. After work of Waldee (1945), on Approved Lists of Bacterial Names and bacteriology manuals in 1980, they were described either under the species named Erwinia or Pectobacterium. The Pectobacterium genus was formally described in 1998 of 265 Pectobacterium strains. Currently, there are 21 species of Pectobacterium bacteria, including Pectobacterium betavasculorum since 2003, which caused soft rot on sugar beet tubers. Based on the biochemical experiments carried out for this, it is known that these bacteria are gram-negative, catalase-positive, oxidase-negative, facultatively anaerobic, using gelatin and causing symptoms of soft rot on potato and sugar beet tubers. The mere fact of growing on sugar beet may indicate a metabolism characteristic only for this species. Metabolomics, broadly defined as the biology of the metabolic systems, which allows to make comprehensive measurements of metabolites. Metabolomics, in combination with genomics, are complementary tools for the identification of metabolites and their reactions, and thus for the reconstruction of metabolic networks. The aim of this study was to apply the GC-MS-based untargeted metabolomics to study the metabolism of P. betavasculorum in different growing conditions. The metabolomic profiles of biomass and biomass media were determined. For sample preparation the following protocol was used: extraction with 900 µl of methanol: chloroform: water mixture (10: 3: 1, v: v) were added to 900 µl of biomass from the bottom of the tube and up to 900 µl of nutrient medium from the bacterial biomass. After centrifugation (13,000 x g, 15 min, 4oC), 300µL of the obtained supernatants were concentrated by rotary vacuum and evaporated to dryness. Afterwards, two-step derivatization procedure was performed before GC-MS analyses. The obtained results were subjected to statistical calculations with the use of both uni- and multivariate tests. The obtained results were evaluated using KEGG database, to asses which metabolic pathways are activated and which genes are responsible for it, during the metabolism of given substrates contained in the growing environment. The observed metabolic changes, combined with biochemical and physiological tests, may enable pathway discovery, regulatory inference and understanding of the homeostatic abilities of P. betavasculorum.

Keywords: GC-MS chromatograpfy, metabolomics, metabolism, pectobacterium strains, pectobacterium betavasculorum

Procedia PDF Downloads 55

Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

Abstract:

New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

Procedia PDF Downloads 21

Authors: Weiping Liu

Abstract:

This paper presents an equation to calculate stock prices of different growth model. This equation is mathematically derived by using discounted cash flow method. It has the advantages of being very easy to use and very accurate. It can still be used even when the first stage is lengthy. This equation is more generalized because it can be used for all the three popular stock price models. It can be programmed into financial calculator or electronic spreadsheets. In addition, it can be extended to a multistage model. It is more versatile and efficient than the traditional methods.

Keywords: stock price, multistage model, different growth model, discounted cash flow method

Procedia PDF Downloads 391

Authors: Abderrahim Siam, Ramdane Maamri, Zaidi Sahnoun

Abstract:

The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines. The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques, and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets

Procedia PDF Downloads 468

Authors: Alok Agrawal, Alok Satapathy

Abstract:

In this paper, an attempt to determine the effective thermal conductivity (keff) of particulate filled polymer composites using finite element method (FEM) a powerful computational technique is made. A commercially available finite element package ANSYS is used for this numerical analysis. Three-dimensional spheres-in-cube lattice array models are constructed to simulate the microstructures of micro-sized particulate filled polymer composites with filler content ranging from 2.35 to 26.8 vol %. Based on the temperature profiles across the composite body, the keff of each composition is estimated theoretically by FEM. Composites with similar filler contents are than fabricated using compression molding technique by reinforcing micro-sized aluminium oxide (Al2O3) in polypropylene (PP) resin. Thermal conductivities of these composite samples are measured according to the ASTM standard E-1530 by using the Unitherm™ Model 2022 tester, which operates on the double guarded heat flow principle. The experimentally measured conductivity values are compared with the numerical values and also with those obtained from existing empirical models. This comparison reveals that the FEM simulated values are found to be in reasonable good agreement with the experimental data. Values obtained from the theoretical model proposed by the authors are also found to be in even closer approximation with the measured values within percolation limit. Further, this study shows that there is gradual enhancement in the conductivity of PP resin with increase in filler percentage and thereby its heat conduction capability is improved. It is noticed that with addition of 26.8 vol % of filler, the keff of composite increases to around 6.3 times that of neat PP. This study validates the proposed model for PP-Al2O3 composite system and proves that finite element analysis can be an excellent methodology for such investigations. With such improved heat conduction ability, these composites can find potential applications in micro-electronics, printed circuit boards, encapsulations etc.

Keywords: analytical modelling, effective thermal conductivity, finite element method, polymer matrix composite

Procedia PDF Downloads 310

Authors: Floriane Shala, Evangeline Wagner, Yichun Zhao

Abstract:

Background: Proper educational training and support are proven to be major components of EHR (Electronic Health Record) implementation and use. However, the majority of health providers are not sufficiently trained in EHR use, leading to adverse events, errors, and decreased quality of care. In response to this, students studying Health Information Science, Public Health, Nursing, and Medicine should all gain a thorough understanding of EHR use at different levels for different purposes. The design of a usable and safe EHR system that accommodates the needs and workflows of different users, user groups, and disciplines is required for EHR learning to be efficient and effective. Objectives: This project builds several artifacts which seek to address both the educational and usability aspects of an educational EHR. The artifacts proposed are models for and examples of such an EHR with a configurable UI to be learned by students who need a background in EHR use during their degrees. Methods: Review literature and gather professional opinions from domain experts on usability, the use of workflow patterns, UI configurability and design, and the educational aspect of EHR use. Conduct interviews in a semi-casual virtual setting with open discussion in order to gain a deeper understanding of the principal aspects of EHR use in educational settings. Select a specific task and user group to illustrate how the proposed solution will function based on the current research. Develop three artifacts based on the available research, professional opinions, and prior knowledge of the topic. The artifacts capture the user task and user’s interactions with the EHR for learning. The first generic model provides a general understanding of the EHR system process. The second model is a specific example of performing the task of MRI ordering with a configurable UI. The third artifact includes UI mock-ups showcasing the models in a practical and visual way. Significance: Due to the lack of educational EHRs, medical professionals do not receive sufficient EHR training. Implementing an educational EHR with a usable and configurable interface to suit the needs of different user groups and disciplines will help facilitate EHR learning and training and ultimately improve the quality of patient care.

Keywords: education, EHR, usability, configurable

Procedia PDF Downloads 146

Authors: Mohamed Moustafa Mahmoud Sedky

Abstract:

The double-fed induction generator wind turbine has recently received a great attention. The steady state performance and response of double fed induction generator (DFIG) based wind turbine are now well understood. This paper presents the analysis of stator and rotor flux linkage dq models operation of DFIG under different faults and at different locations.

Keywords: double fed induction motor, wind energy, flux linkage, short circuit

Procedia PDF Downloads 577