Unsupervised-Learning Assisted Artificial Neural Network for Optimization

Innovations in computer technology made way for Computational Fluid Dynamics (CFD) into engineering, which supported the development of new designs by reducing the cost and time by lowering the dependency on experimentation. There is a further need to make the process of development more efficient. One such technology is Artificial Intelligence. In this thesis, we explore the application of Artificial Intelligence (AI) in CFD and how it can improve the process of development. AI is used as a buzz word for the mechanism which can learn by itself and make the decision accordingly. Machine learning (ML) is a subset of AI which learns any method without the need for any explicit algorithm. Deep Learning is another subset of ML, which is different in its composition. Deep Learning, or Neural Networks (NN), is made up of nodes like the neurons and works on the principle of the human brain. NN can be exploited for any problem without the need for any explicit algorithm for the task. It can be achieved by analyzing and inferring from the observations. Artificial Neural Network (ANN) is used for data analysis and Convolutional Neural Networks (CNN) for image analysis. Our area of interest herein is ANN and its application for a medical equipment called Convective Polymerase Chain Reaction (cPCR) device. Many have relied on engineering experimentation to develop an optimized PCR device, which requires high cost and time. That makes the use of PCR devices less cost-effective as a commonplace for healthcare. We optimize a convective PCR reactor using a high-fidelity CFD-based surrogate model to find an economical and performance-effective one. We plan numerous possible design combinations, evaluating DNA doubling time. Based on these results, an accurate surrogate model is developed for optimization using Deep Learning. We produce two kinds of surrogate models using ANN; one by directly employing ANN and another by using unsupervised learning called, k-Means-Clustering-Assisted ANN, and then compare the results from these two methods. For developing a suitable model of ANN to fit our data, we carry out the analysis of model accuracy and obtain the best design by using a differential evolution method. The best designs obtained by the two methods are verified with the corresponding result obtained from CFD. This shows an effective way of designing an optimized device by reducing the number of CFD simulations required for the development. Consequently, the computational results demonstrate that the convective PCR device can be efficiently developed using our proposed methodology, making it viable for point-of-care applications

Incidence and Predictors of Tuberculosis Among Adult PLWHA at Public Health Facilities of Hawassa City

Tuberculosis (TB) is the most frequently diagnosed opportunistic infection (OI) and disease in people living with HIV/AIDS (PLWHA), world-wide. This study aimed at determining the incidence and predictors of tuberculosis among people living with HIV.A Six year retrospective follow up study was conducted among adult PLHIV. The Cox proportional hazards model was used to identify predictors.A total of 554 patients were followed and produced 1830.3 person year of observation. One hundred sixty one new TB cases occurred during the follow up period. The overall incidence density of TB was 8.79 per 100 person-year (PY). It was high (148.71/100 PY) in the first year of enrolment. The cumulative proportion of TB free survival was 79% and 67% at the end of first and sixth years, respectively. Not having formal education(AHR=2.68, 95%CI: 1.41, 5.11 ), base line WHO clinical stage IV (AHR = 3.22, 95% CI=1.91-5.41), CD4 count <50 cell/ul (AHR=2.41, 95%CI=1.31, 4.42), Being bed redden (AHR= 2.89, 95%CI=1.72, 3.78), past TB history (AHR=1.65, 95% CI = 1.06,2.39), substance use (AHR=1.46, 95% CI=1.03,2.06) and being on pre ART (AHR=1.62, 95%CI:1.03-2.54 ) were independently predicted tuberculosis occurrence. Advanced WHO clinical stage, limited functional status, past TB history, addiction and low CD4 (<50cell/ul) count at enrollment were found to be the independent predictor of tuberculosis occurrence. Therefore early initiation of treatment and intensive follow up is important

The tourism consumption, a special economic category of the final demand in Albania and in the countries of the region

Tourism is an international activity which includes a combination of economic, political, environmental and social factors whose consequences are becoming more and more complex, controversial and which emerge in delicate and unexpected ways. Today tourism is characterized by a development which is not only continuous but also sensitive to rapidly-changing attitudes. The effects of tourism are multifaceted: economic, social, natural or environmental, political, and cultural. In this article we will talk about the effects of the development of tourism on the international and total tourism consumption regarding Albania accompanied with empirical data and a comparison of their respective statistics. We will also try to study the effect of financial crisis on the international tourism consumption in Albania. All the data have been collected from INSTAT and Travel & Tourism Economic Impact 2012, for the time period 2006-2012. The number of visitors to Albania after 2000 has been increasing and consequently the positive impact of tourism on total consumption has become stronger. Nevertheless, after 2006, Albania shows strong fluctuations in tourism consumption compared to other countries in the region. This is due to the fact that Albania is a relatively new destination in the development of tourism market

EDUCATIONAL GAMES AS AN EFFECTIVE TECHNIQUE IN LEARNING OF FOREIGN LANGUAGES

The Purpose of this article is emphasizing the importance of educational games during the process of teaching / learning as one of the most enjoyable tools for children, where they do feel as protagonist. Educational games mean freedom, pleasure, experimentation, manipulation, but also obey and respect the rules, implement strategies and plans, problems solving, discover the unknowns challenge yourself and others. The teacher should use this technique at any stage of teaching / learning process. Endured prepare the games on the diary, even when those are missing in the text book. Educational games means learn by practicing

Bio-based coating of modified limonene via UV light technology

Coating industries expanded the use of petroleum-based commodities for better coating properties, which is rising the pollution concern. In this research, bio-based material such as limonene was used to deplete the usage of petroleum raw-material for coating. Limonene-polyol was prepared through a thiol-ene reaction and then methacrylate with methacrylic anhydride via esterification reaction to proceed further for UV curing formulation. As per FT-IR examination, hydroxyl functional groups held by the structure of limonene were transfigured into the corresponding methacrylate and by analysis of C=C peak after curing, cure percentage was noticed near to 92%. The methacrylated limonene-polyol was formulated for UV curing through the addition of a photoinitiator and an alternate measure of cross-linker, where this combination was applied to a steel surface and relieved under UV light to give a cross-linked formation, which gives solid surface grip and scratch-resistant coating. The coated material was also characterized by FT-IR, thermal, tensile, flexural test whereas results give strong tensile strength about 79 MPa by increasing the 30% of the amount of methacrylated limonene-polyol and banding modulus (flexural) observed 38 GPa. Alter the amount of methacrylated limonene-polyol was also tested. This research presents a convenient synthesis procedure for coating applications by using bio-based material at a lower cost

Electrochemical properties of MOF-derived nickel compounds for high performance supercapacitor and electrocatalysts

There are many different ways that energy is used in daily life. From applications that require a high energy density to long-term storage in a stable manner, the requirements for energy usage are diverse. Therefore, the greater the number of uses a designed material exhibit, the more practical it may be for wide-scale manufacture. An emerging class of functional porous materials referred to as metal-organic framework (MOF) has received considerable attention over the past two decades, partially because of their potential use in a wide variety of applications, including gas storage, molecular separations, water splitting, and supercapacitor devices. In addition, an electrode material with high performance as an essential part is highly desirable for supercapacitors. Herein, we synthesize the nickel-MOF (Ni-MIL-77) via an in-situ synthesis route using glutaric acid in a hydrothermal process at different temperatures @ 140, 160, and 180 °C. As an electrocatalyst for hydrogen evolution reaction (HER), Ni-MIL-77@140 displayed the lowest overpotential of 126 mV. On the other hand, Ni-MIL-77@160 showed the lowest overpotential of 330 mV among all samples for oxygen evolution reactions (OER). In terms of energy storage, the Ni-MIL-77@160 had the highest specific capacitance of 603 F/g at a current density of 1 A/g with an energy density of 25 W-h/kg and power density of 272 W/kg. This works offers the facile way to rationally design and synthesize the MOF-based electrodes for powerful and stable supercapacitor and also the efficient way for water splitting

Germline genetic variation in prostate susceptibility does not predict outcomes in the chemoprevention trials PCPT and SELECT

Background The development of prostate cancer can be influenced by genetic and environmental factors. Numerous germline SNPs influence prostate cancer susceptibility. The functional pathways in which these SNPs increase prostate cancer susceptibility are unknown. Finasteride is currently not being used routinely as a chemoprevention agent but the long term outcomes of the PCPT trial are awaited. The outcomes of the SELECT trial have not recommended the use of chemoprevention in preventing prostate cancer. This study investigated whether germline risk SNPs could be used to predict outcomes in the PCPT and SELECT trial. Methods Genotyping was performed in European men entered into the PCPT trial (n = 2434) and SELECT (n = 4885). Next generation genotyping was performed using Affymetrix® Eureka™ Genotyping protocols. Logistic regression models were used to test the association of risk scores and the outcomes in the PCPT and SELECT trials. Results Of the 100 SNPs, 98 designed successfully and genotyping was validated for samples genotyped on other platforms. A number of SNPs predicted for aggressive disease in both trials. Men with a higher polygenic score are more likely to develop prostate cancer in both trials, but the score did not predict for other outcomes in the trial. Conclusion Men with a higher polygenic risk score are more likely to develop prostate cancer. There were no interactions of these germline risk SNPs and the chemoprevention agents in the SELECT and PCPT trials

Predictors of Neonatal mortality among Neonates who admitted in Neonatal intensive Care Unit at Arba Minch General Hospital

Introduction: The neonatal period refers to the first 28 days of life. Newborns are particularly vulnerable to death. The predictors associated with neonatal mortality need to be addressed, as identifying the predictors will contribute to reducing the rates of neonatal morbidity and mortality.Method: A facility-based retrospective cohort study was conducted of 332 records of neonates who were admitted to the neonatal intensive care unit at Arba Minch General Hospital. Data were collected from randomly selected neonate records using computer-generated random numbers. Data were entered into Epi-info version 3.5.1 and exported to SPSS v.23 for analysis. Crude hazard ratios, adjusted hazard ratios and 95% confidence intervals were used to assess the strength of association and statistical significance. The incidence density rate of death with respect to ‘person time at risk’ was calculated. Variables which had a p-value of ≤ 0.25 in bivariate analysis were considered as candidates for multivariate regression analysis; variables that had a p-value of ≤0.05 in the multivariate analysis were considered as independent predictors of neonatal mortality in the final Cox regression analysis.Result: The incidence density rate of neonatal mortality was 31.6 per 1,000 neonate days. The neonatal mortality predictors were 5th-minute APGAR score ≤5 (AHR: 1.9; 95%CI: 1.02,3.54); 2nd to 4th birth order (AHR:13; 95%CI: 5.1,33.4); 5th birth order (AHR:24; 95%CI: 10.5,55.2); history of two to four live births(AHR: 0.16; 95%CI: 1.07,3.63); history of ≥5 live births (AHR: 0.18; 95%CI: 0.06,0.51); and not initiating exclusive breastfeeding within the first hour of delivery (AHR: 1.8: 95%CI: 1.03,3.18).Conclusion: The incidence density rate of neonatal mortality was 31.6 per 1,000 neonate days, and maternal age, APGAR score, birth order, parity, and exclusive breastfeeding initiation were independent predictors of neonatal mortality. [Ethiop.J. Health Dev. 2019; 33(1):46-52]Key words: Neonatal mortality; Predictors; Arba Minch General hospita

Bio-based polyurethanes foams: Effects of green flame-retardants

The wide range of physical and chemical properties of polyurethanes make them one of the most popular polymers for industrial applications. Polyurethanes are synthesized using isocyanates, polyols, surfactants, additives, and catalysts. Polyurethane foams can be rigid or flexible and find vast applications in the automotive, construction, furniture, and medical industries. Despite the numerous applications of polyurethanes, their high flammability is a major concern for their safe use in many applications. In addition, current research seeks renewable sources such as vegetable oils and other biomass for polyurethane synthesis. In our research, highly flame-retardant polyurethane foams using bio-derived polyol were prepared and characterized. Sunflower oil was used in the synthesis of a bio-based polyol as an alternative to petroleum-based polyols. Epoxidation followed by ring-opening reactions were carried out to synthesize the sunflower oil polyol whose formation was confirmed with other tests. Expandable graphite (EG) and dimethyl methylphosphonate (DMMP) which are non-halogenated flame retardants were used in varying concentrations for the preparation of bio-based rigid polyurethane foams. The effects of these flame retardants on the physicomechanical properties and flame retardancy of the sunflower-based foams were studied. Mechanical and thermogravimetric analysis showed that the foams had a high compressive strength along with high thermal stability. The closed-cell contents of the foams were over 90% with a uniform distribution of cell size. The burning test revealed a significant effect of the flame-retardants on the flammability of the foams. And with the addition of EG, the burning weight loss time was reduced from 80 s to 4 s and that of DMMP from 70 s to 3 s. Our research suggests that sunflower oil could be a potential candidate for the polyurethane industries and the use of non-halogenated DMMP or EG can serve as green and effective flame-retardants in bio-based polyurethane foams