Search results for: disease prediction
2410 Procedural Protocol for Dual Energy Computed Tomography (DECT) Inversion
Authors: Rezvan Ravanfar Haghighi, S. Chatterjee, Pratik Kumar, V. C. Vani, Priya Jagia, Sanjiv Sharma, Susama Rani Mandal, R. Lakshmy
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The dual energy computed tomography (DECT) aims at noting the HU(V) values for the sample at two different voltages V=V1, V2 and thus obtain the electron densities (ρe) and effective atomic number (Zeff) of the substance. In the present paper, we aim to obtain a numerical algorithm by which (ρe, Zeff) can be obtained from the HU(100) and HU(140) data, where V=100, 140 kVp. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques.With the idea to develop the inversion algorithm for low Zeff materials, as is the case with non calcified coronary artery plaque, we prepare aqueous samples whose calculated values of (ρe, Zeff) lie in the range (2.65×1023≤ ρe≤ 3.64×1023 per cc ) and (6.80≤ Zeff ≤ 8.90). We fill the phantom with these known samples and experimentally determine HU(100) and HU(140) for the same pixels. Knowing that the HU(V) values are related to the attenuation coefficient of the system, we present an algorithm by which the (ρe, Zeff) is calibrated with respect to (HU(100), HU(140)). The calibration is done with a known set of 20 samples; its accuracy is checked with a different set of 23 known samples. We find that the calibration gives the ρe with an accuracy of ± 4% while Zeff is found within ±1% of the actual value, the confidence being 95%.In this inversion method (ρe, Zeff) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (ρe, Zeff) does not interfere with each other. It is found that this algorithm can be used for prediction of chemical characteristic (ρe, Zeff) of unknown scanned materials with 95% confidence level, by inversion of the DECT data.Keywords: chemical composition, dual-energy computed tomography, inversion algorithm
Procedia PDF Downloads 4382409 Pancreatic Lipase and Cholesterol Esterase Inhibitors from Thai Medicinal Plants
Authors: Kwanchai Ratanamanee, Pattra Ahmadi Pirshahid, Yaowaluk Khamphan, Sirinan Thubthimthad
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Obesity is a main global health problem. The obesity rated has continued to be higher and higher. It causes to serious systems, diabetes, coronary artery disease, stroke, and some types of cancer. Oristat is one of the best drugs worldwide used as a pancreatic lipase inhibitor. To develop the new therapeutic drugs from medicinal plant always explored. In this study, 24 medicinal plants were investigated for their pancreatic lipase and cholesterol esterase inhibitory effects with Fluorometer assay and oristat as a positive control. It showed that the ethanolic extract of pods of Acacia concinna (Willd.) D.C., possess pancreatic lipase and cholesterol esterase inhibitory activities of IC50 at 2.73 and 3.77 mg/ml respectively as well as oral acute toxicity of the extract (LD50) was 6,300 mg/kg body weight. The extract of A.concinna should be further investigated in animal testing. The results of pancreatic lipase and cholesterol esterase inhibitor of the extracts will lead us to utilize A.concinna for developing as obesity dietary supplement from a medicinal plant.Keywords: Acacia concinna (Willd.) D. C., cholesterol esterase, obesity, pancreatic lipase
Procedia PDF Downloads 4782408 Estimation of the Length and Location of Ground Surface Deformation Caused by the Reverse Faulting
Authors: Nader Khalafian, Mohsen Ghaderi
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Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.Keywords: reverse faulting, surface deformation, numerical, neural network
Procedia PDF Downloads 4212407 Determination of Direct Solar Radiation Using Atmospheric Physics Models
Authors: Pattra Pukdeekiat, Siriluk Ruangrungrote
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This work was originated to precisely determine direct solar radiation by using atmospheric physics models since the accurate prediction of solar radiation is necessary and useful for solar energy applications including atmospheric research. The possible models and techniques for a calculation of regional direct solar radiation were challenging and compulsory for the case of unavailable instrumental measurement. The investigation was mathematically governed by six astronomical parameters i.e. declination (δ), hour angle (ω), solar time, solar zenith angle (θz), extraterrestrial radiation (Iso) and eccentricity (E0) along with two atmospheric parameters i.e. air mass (mr) and dew point temperature at Bangna meteorological station (13.67° N, 100.61° E) in Bangkok, Thailand. Analyses of five models of solar radiation determination with the assumption of clear sky were applied accompanied by three statistical tests: Mean Bias Difference (MBD), Root Mean Square Difference (RMSD) and Coefficient of determination (R2) in order to validate the accuracy of obtainable results. The calculated direct solar radiation was in a range of 491-505 Watt/m2 with relative percentage error 8.41% for winter and 532-540 Watt/m2 with relative percentage error 4.89% for summer 2014. Additionally, dataset of seven continuous days, representing both seasons were considered with the MBD, RMSD and R2 of -0.08, 0.25, 0.86 and -0.14, 0.35, 3.29, respectively, which belong to Kumar model for winter and CSR model for summer. In summary, the determination of direct solar radiation based on atmospheric models and empirical equations could advantageously provide immediate and reliable values of the solar components for any site in the region without a constraint of actual measurement.Keywords: atmospheric physics models, astronomical parameters, atmospheric parameters, clear sky condition
Procedia PDF Downloads 4092406 Proposal Method of Prediction of the Early Stages of Dementia Using IoT and Magnet Sensors
Authors: João Filipe Papel, Tatsuji Munaka
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With society's aging and the number of elderly with dementia rising, researchers have been actively studying how to support the elderly in the early stages of dementia with the objective of allowing them to have a better life quality and as much as possible independence. To make this possible, most researchers in this field are using the Internet Of Things to monitor the elderly activities and assist them in performing them. The most common sensor used to monitor the elderly activities is the Camera sensor due to its easy installation and configuration. The other commonly used sensor is the sound sensor. However, we need to consider privacy when using these sensors. This research aims to develop a system capable of predicting the early stages of dementia based on monitoring and controlling the elderly activities of daily living. To make this system possible, some issues need to be addressed. First, the issue related to elderly privacy when trying to detect their Activities of Daily Living. Privacy when performing detection and monitoring Activities of Daily Living it's a serious concern. One of the purposes of this research is to achieve this detection and monitoring without putting the privacy of the elderly at risk. To make this possible, the study focuses on using an approach based on using Magnet Sensors to collect binary data. The second is to use the data collected by monitoring Activities of Daily Living to predict the early stages of Dementia. To make this possible, the research team suggests developing a proprietary ontology combined with both data-driven and knowledge-driven.Keywords: dementia, activity recognition, magnet sensors, ontology, data driven and knowledge driven, IoT, activities of daily living
Procedia PDF Downloads 1052405 A Convolutional Neural Network-Based Model for Lassa fever Virus Prediction Using Patient Blood Smear Image
Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa
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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever
Procedia PDF Downloads 1202404 Enhancing Rupture Pressure Prediction for Corroded Pipes Through Finite Element Optimization
Authors: Benkouiten Imene, Chabli Ouerdia, Boutoutaou Hamid, Kadri Nesrine, Bouledroua Omar
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Algeria is actively enhancing gas productivity by augmenting the supply flow. However, this effort has led to increased internal pressure, posing a potential risk to the pipeline's integrity, particularly in the presence of corrosion defects. Sonatrach relies on a vast network of pipelines spanning 24,000 kilometers for the transportation of gas and oil. The aging of these pipelines raises the likelihood of corrosion both internally and externally, heightening the risk of ruptures. To address this issue, a comprehensive inspection is imperative, utilizing specialized scraping tools. These advanced tools furnish a detailed assessment of all pipeline defects. It is essential to recalculate the pressure parameters to safeguard the corroded pipeline's integrity while ensuring the continuity of production. In this context, Sonatrach employs symbolic pressure limit calculations, such as ASME B31G (2009) and the modified ASME B31G (2012). The aim of this study is to perform a comparative analysis of various limit pressure calculation methods documented in the literature, namely DNV RP F-101, SHELL, P-CORRC, NETTO, and CSA Z662. This comparative assessment will be based on a dataset comprising 329 burst tests published in the literature. Ultimately, we intend to introduce a novel approach grounded in the finite element method, employing ANSYS software.Keywords: pipeline burst pressure, burst test, corrosion defect, corroded pipeline, finite element method
Procedia PDF Downloads 582403 Prediction of Compressive Strength of Concrete from Early Age Test Result Using Design of Experiments (Rsm)
Authors: Salem Alsanusi, Loubna Bentaher
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Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates ‘finding the flats’ on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarse-aggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.Keywords: mix proportioning, response surface methodology, compressive strength, optimal design
Procedia PDF Downloads 2672402 Determining the Relationship Between Maternal Stress and Depression and Child Obesity: The Mediating Role of Maternal Self-efficacy
Authors: Alireza Monzavi Chaleshtori, Mahnaz Aliakbari Dehkordi, Maryam Aliakbari, Solmaz Seyed Mostafaii
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Objective: Considering the growing obesity among children and the role of mother's psychological factors as well as the need to prevent childhood obesity, this study aimed to investigate the mediating role of mother's self-efficacy in the relationship between mother's stress and depression and child obesity. Method: For this purpose, in a descriptive-correlation study, 222 mothers and children aged 1 to 5 years in Tehran, who had the opportunity to answer an online questionnaire, were selected by random sampling and to the depression scales of the Kroenke and Spitzer Patient Health Questionnaire, Cohen's stress and Self-efficacy of Berkeley mothers answered. Pearson correlation test and path analysis were used for data analysis. Findings: The findings showed that maternal depression had an indirect and significant effect on child obesity, and the effect of stress and depression on child obesity was indirect and non-significant. Therefore, the model has a good fit with the research data, and stress and depression indirectly predicted child obesity with the mediating role of self-efficacy. Conclusion: The hypothesized model tested based on mother's stress and depression with the mediating role of mother's self-efficacy was a good model in explaining the prediction of child obesity. Based on the findings of this research, a practical framework can be provided to explain the psychological factors of the mother in relation to child obesity and its treatment.Keywords: stress, self-efficacy, child obesity, depression
Procedia PDF Downloads 712401 A Flute Tracking System for Monitoring the Wear of Cutting Tools in Milling Operations
Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay
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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.Keywords: machining, milling operation, tool condition monitoring, tool wear prediction
Procedia PDF Downloads 3032400 Human Mesenchymal Stem Cells as a Potential Source for Cell Therapy in Liver Disorders
Authors: Laila Montaser, Hala Gabr, Maha El-Bassuony, Gehan Tawfeek
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Orthotropic liver transplantation (OLT) is the final procedure of both end stage and metabolic liver diseases. Hepatocyte transplantation is an alternative for OLT, but the sources of hepatocytes are limited. Bone marrow mesenchymal stem cells (BM-MSCs) can differentiate into hepatocyte-like cells and are a potential alternative source for hepatocytes. The MSCs from bone marrow are a promising target population as they are capable of differentiating along multiple lineages and, at least in vitro, have significant expansion capability. MSCs from bone marrow may have the potential to differentiate in vitro and in vivo into hepatocytes. Our study examined whether mesenchymal stem cells (MSCs), which are stem cells originated from human bone marrow, are able to differentiate into functional hepatocyte-like cells in vitro. Our aim was to investigate the differentiation potential of BM-MSCs into hepatocyte-like cells. Adult stem cell therapy could solve the problem of degenerative disorders, including liver disease.Keywords: bone marrow, differentiation, hepatocyte, stem cells
Procedia PDF Downloads 5202399 Feeding Patterns and Diarrhea Incidence Among Children in Bangladesh: A Study Using Data from Demographic and Health Survey, 2014
Authors: Iqbal Ahmed Chowdhury
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Diarrhea is considered to be one of the influential factors of child death in Bangladesh. While it is known that diarrhea is a water-driven disease, due to the lack of studies, little is known about the extent to which various feeding patterns contribute to such an incidence. Our paper intends to fill this gap by looking into different feeding patterns and their influence on diarrhea incidence among children in Bangladesh. Using data collected for the Demographic and Health Survey, 2014, this paper reveals that feeding patterns can influence the diarrhea incidence among this group of children to a great extent. This paper finds that the incidence of diarrhea is likely to elevate if diarrhea-affected children are fed plain water from any source and any kind of juice. However, breastfeeding, feeding soup or clear broth, prescribed baby food, and clean water from a tube well tend to help fight diarrhea incidence among children in Bangladesh. The results are found to be consistent even after controlling for sociodemographic variables, including age and sex of children, age and education qualification of the parent, and the number of children in the family. The results of this study could contribute to treating diarrhea among children in Bangladesh as well as similar other countries in the world.Keywords: feeding patterns, diarrhea, Bangladesh, children
Procedia PDF Downloads 1092398 Protective Effect of the Standardized Extract of Holmskioldia sanguinea on Tumor Bearing Mice
Authors: Mahesh Pal, Tripti Mishra, Chandana Rao, Dalip Upreti
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Cancer has been considered to be a very dreadful disease. Holmskioldia sanguinea is a large climbing shrub found in the Himalayas at an altitude of 5,000 ft and preliminary investigation showed the excellent yield of andrographolide and subjected for the anticancer activity. Protective effect of Holmskioldia sanguinea leaf ethanolic extract has been investigated against Ehrlich ascites carcinoma (EAC) and Daltons ascites lymphoma (DAL) in Swiss albino mice to evaluate the possible mechanism of action. The enzymatic antioxidant status was studied on tumor bearing mice, which shows the potential of the compound to possess significant free radical scavenging property and revealed significant tumor regression and prolonged survival time. The isolated bioactive molecule andrographolide from Holmskioldia sanguinea yields (2.5%) in subject to HPTLC/HPLC analysis. The cellular defense system constituting the superoxide dismutase, catalyses was enhanced whereby the lipid peroxidation content was restricted to a larger extent. The Holmskioldia sanguinea is a new source of andrographolide and demonstrated the potency in treatment of cancer.Keywords: Holmskioldia sanguinea, tumor, mice, andrographolide
Procedia PDF Downloads 2642397 Disease Characteristics of Neurofibromatosis Type II and Cochlear Implantation
Authors: Boxiang Zhuang
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This study analyzes the clinical manifestations, hearing rehabilitation methods and outcomes of a complex case of neurofibromatosis type II (NF2). Methods: The clinical manifestations, medical history, clinical data, surgical methods and postoperative hearing rehabilitation outcomes of an NF2 patient were analyzed to determine the hearing reconstruction method and postoperative effect for a special type of NF2 acoustic neuroma. Results: The patient had bilateral acoustic neuromas with profound sensorineural hearing loss in both ears. Peripheral blood genetic testing did not reveal pathogenic gene mutations, suggesting mosaicism. The patient had an intracochlear schwannoma in the right ear and severely impaired vision in both eyes. Cochlear implantation with tumor retention was performed in the right ear. After 2 months of family-based auditory and speech rehabilitation, the Categories of Auditory Performance (CAP) score improved from 0 to 5. Conclusion: NF2 has complex clinical manifestations and poor prognosis. For NF2 patients with intracochlear tumors, cochlear implantation with tumor retention can be used to reconstruct hearing.Keywords: NF2, intracochlear schwannoma, hearing reconstruction, cochlear implantation
Procedia PDF Downloads 132396 Effects of an Educational Program on Nurses Knowledge and Practice Related to Hepatitis-B: Pre-Experimental Design
Authors: R. S. Mehta, G. N. Mandal
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Hepatitis-B is the major infectious disease of mankind. In Nepal it is reported that more than 4.3% of Nepalese population at any time in their life has been infected with Hepatitis-B virus (HBV). The objective of this study was to evaluate the effectiveness of planned educational programme regarding knowledge and practice of hepatitis-B among the nurses working at medical units of BPKIHS. Pre-experimental research design was used to conduct the study among the nurses working in medical units of BPKIHS. Total 40 nurses were included in the pre-test and 34 in the post-test. The education intervention was arranged on 24th May 2012 from 2:15 pm to 4:45 pm i.e. two and half hours. After two weeks of education intervention post-test was conducted. Most of the participants (60%) were of the age group of 18-22 years, Hindu (82.5%), and unmarried (65%). After education intervention there is significant differences in knowledge on the components of Hepatitis-B at 0.05 level of significance. There is no difference in the attitude components after post-test except the component patient contaminated with Hepatitis-B must be called as the last patient (p=0.035). It can conclude that hepatitis-B educational program improved knowledge and practice among the nurses.Keywords: educational program, Hepatitis-B, pre-experimental design, medical units
Procedia PDF Downloads 3572395 Utilizing Street Medicine to Reduce Communicable Disease Prevalence in a Cost-Effective Way
Authors: Bailey Hall, Athena Hoppe, Tevyn Kagele, Anna Nichols, Breeanna Messner
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The Spokane Street Medicine (SSM) Program aims to deliver medical care to people experiencing homelessness in Spokane, Washington. Street medicine is designed to function in a non-traditional setting to help deliver healthcare to a largely underserved population. In this analysis, the SSM Program’s medical charts from street and shelter encounters in early 2021 were reviewed in order to identify illness and diseases in people experiencing homelessness in Spokane. More than half of the prescriptions written during these encounters were for either an antibacterial, an antibiotic, or an antifungal. Estimates of the cost to the local healthcare system are included. Initiating treatment for communicable diseases in people experiencing homelessness via street medicine efforts greatly reduces economic costs while improving health outcomes.Keywords: ethical issues in public health, equity issues in public health, health economics, health disparities, healthcare costs, medical public health, public health ethics, street medicine
Procedia PDF Downloads 1892394 Composite Approach to Extremism and Terrorism Web Content Classification
Authors: Kolade Olawande Owoeye, George Weir
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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.Keywords: sentiposit, classification, extremism, terrorism
Procedia PDF Downloads 2782393 Epidemiology, Prevention and Treatment of Leishmaniasis in Afghanistan
Authors: Mohammad Reza Mohammadi, Layegheh Daliri
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Introduction: Leishmaniasis occurs in infectious diseases of Leishmania protozoa in Afghanistan, anthroponotic leishmaniasis and common cutaneous leishmaniasis (ZCL). Anthroponotic skin leishmania tropica may cause urban diseases and transmitted by Phlebotomus Sergenti. In different parts of Afghanistan, different species of Leishmania are observed. We report the epidemiological characteristics of prevention and treatment in this study. Methods: This study examines the epidemiology and prevention of religious diseases in Afghanistan. Knowledge gaps were analyzed and collected with our own data. Results: In Afghanistan, most of the Lishmania Tropic seekers are Four species of Leishmania in northern Afghanistan, including Leishmania Tropica, L. Major and L. Donovani, cause skin lesions, but L. Donovani and L. infantum are visible. Even combined prevention can significantly reduce the amount of infection. Conclusion: Skinny, as well as visceral leishmaniasis, can occur among the returnees from Afghanistan. Unusual and poor skin lesions can be created by L. Donovani. In most pathogenic areas, the transmission of common diseases between humans and animals. Home dogs are the main reservoir, transferring in some areas such as India and Sudan.Keywords: leishmania donovani, leishmania tropica, treatment, disease, epidemiology
Procedia PDF Downloads 1822392 In silico and Toxicity Study of the Combination of Roselle (Hibiscus sabdariffa L.) and Garlic (Allium sativum L.) as Antihypertensive Herbs
Authors: Doni Dermawan
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Hypertension is a disease with a high prevalence in Indonesia. The prevalence of hypertension in Indonesia is based on the Basic Health Research (Riskesdas) in 2013 which amounted to 25.8%. Medicinal plants have been widely used to treat hypertension including roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) by a mechanism as angiotensin converting enzyme (ACE) inhibitor. The purpose of this research is to analyze the in silico (molecular studies) of pharmacological effects and toxicity of roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) as well as a combination of both are used as antihypertensive herbs. The results of study showed that roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) have great potential as antihypertensive herbs based on the affinity and stability of active substances to specific receptor with a much better value than a of antihypertensive drugs (lisinopril). Toxicity values determined by the method of AST, ALT and ALP in which the three values obtained indicate the presence of acute toxic effects that need to be considered in determining the dose of the extract of roselle and garlic as antihypertensives.Keywords: Allium sativum, antihypertensive, Hibiscus sabdariffa, in silico, toxicity
Procedia PDF Downloads 3422391 Size Effect on Shear Strength of Slender Reinforced Concrete Beams
Authors: Subhan Ahmad, Pradeep Bhargava, Ajay Chourasia
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Shear failure in reinforced concrete beams without shear reinforcement leads to loss of property and life since a very little or no warning occurs before failure as in case of flexural failure. Shear strength of reinforced concrete beams decreases as its depth increases. This phenomenon is generally called as the size effect. In this paper, a comparative analysis is performed to estimate the performance of shear strength models in capturing the size effect of reinforced concrete beams made with conventional concrete, self-compacting concrete, and recycled aggregate concrete. Four shear strength models that account for the size effect in shear are selected from the literature and applied on the datasets of slender reinforced concrete beams. Beams prepared with conventional concrete, self-compacting concrete, and recycled aggregate concrete are considered for the analysis. Results showed that all the four models captured the size effect in shear effectively and produced conservative estimates of the shear strength for beams made with normal strength conventional concrete. These models yielded unconservative estimates for high strength conventional concrete beams with larger effective depths ( > 450 mm). Model of Bazant and Kim (1984) captured the size effect precisely and produced conservative estimates of shear strength of self-compacting concrete beams at all the effective depths. Also, shear strength models considered in this study produced unconservative estimates of shear strength for recycled aggregate concrete beams at all effective depths.Keywords: reinforced concrete beams; shear strength; prediction models; size effect
Procedia PDF Downloads 1612390 Exercise program’s Effectiveness on Hepatic Fat Mobilization among Nonalcoholic Fatty Liver Patients
Authors: Taher Eid Shaaban Ahmed Mousa
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Non-Alcoholic fatty liver disease (NAFLD) is a major cause of multiple liver disorders, which strongly linked to a poor lifestyle. This study aiming to elucidate the exercise program’s effectiveness on hepatic fat mobilization among nonalcoholic fatty liver patients. Subjects: A purposive sample of 150 adult male & female patients. Setting: National institute of liver out patient's clinics of Menoufia University. Tools: three tools I: An interviewing structured questionnaire, II: International Physical Activity Questionnaire, III: compliance assessment sheet. Results: There was statistically significant difference pre and post exercise program regarding total body weight, physical activity level and compliance that prevent new fat development with resolution of existing one. Conclusion: regular exercise is the best implemented approach as an initial step for the prevention, treatment and management of NAFLD. Recommendation: It is highly important to unravel the mechanism and dose by which each exercise specifically resolve various stages of liver diseases.Keywords: exercise program, hebatic fat mobilization, nonalcoholic fatty liver patients, sport science
Procedia PDF Downloads 852389 Light-Weight Network for Real-Time Pose Estimation
Authors: Jianghao Hu, Hongyu Wang
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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone
Procedia PDF Downloads 1542388 The Effects of Circadian Rhythms Change in High Latitudes
Authors: Ekaterina Zvorykina
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Nowadays, Arctic and Antarctic regions are distinguished to be one of the most important strategic resources for global development. Nonetheless, living conditions in Arctic regions still demand certain improvements. As soon as the region is rarely populated, one of the main points of interest is health accommodation of the people, who migrate to Arctic region for permanent and shift work. At Arctic and Antarctic latitudes, personnel face polar day and polar night conditions during the time of the year. It means that they are deprived of natural sunlight in winter season and have continuous daylight in summer. Firstly, the change in light intensity during 24-hours period due to migration affects circadian rhythms. Moreover, the controlled artificial light in winter is also an issue. The results of the recent studies on night shift medical professionals, who were exposed to permanent artificial light, have already demonstrated higher risks in cancer, depression, Alzheimer disease. Moreover, people exposed to frequent time zones change are also subjected to higher risks of heart attack and cancer. Thus, our main goals are to understand how high latitude work and living conditions can affect human health and how it can be prevented. In our study, we analyze molecular and cellular factors, which play important role in circadian rhythm change and distinguish main risk groups in people, migrating to high latitudes. The main well-studied index of circadian timing is melatonin or its metabolite 6-sulfatoxymelatonin. In low light intensity melatonin synthesis is disturbed and as a result human organism requires more time for sleep, which is still disregarded when it comes to working time organization. Lack of melatonin also causes shortage in serotonin production, which leads to higher depression risk. Melatonin is also known to inhibit oncogenes and increase apoptosis level in cells, the main factors for tumor growth, as well as circadian clock genes (for example Per2). Thus, people who work in high latitudes can be distinguished as a risk group for cancer diseases and demand more attention. Clock/Clock genes, known to be one of the main circadian clock regulators, decrease sensitivity of hypothalamus to estrogen and decrease glucose sensibility, which leads to premature aging and oestrous cycle disruption. Permanent light exposure also leads to accumulation superoxide dismutase and oxidative stress, which is one of the main factors for early dementia and Alzheimer disease. We propose a new screening system adjusted for people, migrating from middle to high latitudes and accommodation therapy. Screening is focused on melatonin and estrogen levels, sleep deprivation and neural disorders, depression level, cancer risks and heart and vascular disorders. Accommodation therapy includes different types artificial light exposure, additional melatonin and neuroprotectors. Preventive procedures can lead to increase of migration intensity to high latitudes and, as a result, the prosperity of Arctic region.Keywords: circadian rhythm, high latitudes, melatonin, neuroprotectors
Procedia PDF Downloads 1562387 Machine Learning Models for the Prediction of Heating and Cooling Loads of a Residential Building
Authors: Aaditya U. Jhamb
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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.Keywords: energy efficient buildings, heating load, cooling load, machine learning models
Procedia PDF Downloads 962386 Development of GIS-Based Geotechnical Guidance Maps for Prediction of Soil Bearing Capacity
Authors: Q. Toufeeq, R. Kauser, U. R. Jamil, N. Sohaib
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Foundation design of a structure needs soil investigation to avoid failures due to settlements. This soil investigation is expensive and time-consuming. Developments of new residential societies involve huge leveling of large sites that is accompanied by heavy land filling. Poor practices of land fill for deep depths cause differential settlements and consolidations of underneath soil that sometimes result in the collapse of structures. The extent of filling remains unknown to the individual developer unless soil investigation is carried out. Soil investigation cannot be performed on each available site due to involved costs. However, fair estimate of bearing capacity can be made if such tests are already done in the surrounding areas. The geotechnical guidance maps can provide a fair assessment of soil properties. Previously, GIS-based approaches have been used to develop maps using extrapolation and interpolations techniques for bearing capacities, underground recharge, soil classification, geological hazards, landslide hazards, socio-economic, and soil liquefaction mapping. Standard penetration test (SPT) data of surrounding sites were already available. Google Earth is used for digitization of collected data. Few points were considered for data calibration and validation. Resultant Geographic information system (GIS)-based guidance maps are helpful to anticipate the bearing capacity in the real estate industry.Keywords: bearing capacity, soil classification, geographical information system, inverse distance weighted, radial basis function
Procedia PDF Downloads 1352385 Glycyrrhizic Acid Inhibits Lipopolysaccharide-Stimulated Bovine Fibroblast-Like Synoviocyte, Invasion through Suppression of TLR4/NF-κB-Mediated Matrix Metalloproteinase-9 Expression
Authors: Hosein Maghsoudi
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Rheumatois arthritis (RA) is progressive inflammatory autoimmune diseases that primarily affect the joints, characterized by synovial hyperplasia and inflammatory cell infiltration, deformed and painful joints, which can lead tissue destruction, functional disability systemic complications, and early dead and socioeconomic costs. The cause of rheumatoid arthritis is unknown, but genetic and environmental factors are contributory and the prognosis is guarded. However, advances in understanding the pathogenesis of the disease have fostered the development of new therapeutics, with improved outcomes. The current treatment strategy, which reflects this progress, is to initiate aggressive therapy soon after diagnosis and to escalate the therapy, guided by an assessment of disease activity, in pursuit of clinical remission. The pathobiology of RA is multifaceted and involves T cells, B cells, fibroblast-like synoviocyte (FLSc) and the complex interaction of many pro-inflammatory cytokine. Novel biologic agents that target tumor necrosis or interlukin (IL)-1 and Il-6, in addition T- and B-cells inhibitors, have resulted in favorable clinical outcomes in patients with RA. Despite this, at least 30% of RA patients are résistance to available therapies, suggesting novel mediators should be identified that can target other disease-specific pathway or cell lineage. Among the inflammatory cell population that might participated in RA pathogenesis, FLSc are crucial in initiaing and driving RA in concert of cartilage and bone by secreting metalloproteinase (MMPs) into the synovial fluid and by direct invasion into extracellular matrix (ECM), further exacerbating joint damage. Invasion of fibroblast-like synoviocytes (FLSc) is critical in the pathogenesis of rheumatoid-arthritis. The metalloproteinase (MMPs) and activator of Toll-like receptor 4 (TLR4)/nuclear factor- κB pthway play a critical role in RA-FLS invasion induced by lipopolysaccharide (LPS). The present study aimed to explore the anti-invasion activity of Glycyrrhizic Acid as a pharmacologically safe phytochemical agent with potent anti-inflammatory properties on IL-1beta and TNF-alpha signalling pathways in Bovine fibroblast-like synoviocyte ex- vitro, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Results showed that Glycyrrhizic Acid suppressed LPS-stimulated bovine FLS migration and invasion by inhibition MMP-9 expression and activity. In addition our results revealed that Glycyrrhizic Acid inhibited the transcriptional activity of MMP-9 by suppression the nbinding activity of NF- κB in the MMP-9 promoter pathway. The extract of licorice (Glycyrrhiza glabra L.) has been widely used for many centuries in the traditional Chinese medicine as native anti-allergic agent. Glycyrrhizin (GL), a triterpenoidsaponin, extracted from the roots of licorice is the most effective compound for inflammation and allergic diseases in human body. The biological and pharmacological studies revealed that GL possesses many pharmacological effects, such as anti-inflammatory, anti-viral and liver protective effects, and the biological effects, such as induction of cytokines (interferon-γ and IL-12), chemokines as well as extrathymic T and anti-type 2 T cells. GL is known in the traditional Chinese medicine for its anti-inflammatory effect, which is originally described by Finney in 1959. The mechanism of the GL-induced anti-inflammatory effect is based on different pathways of the GL-induced selective inhibition of the prostaglandin E2 production, the CK-II- mediated activation of both GL-binding lipoxygenas (gbLOX; 17) and PLA2, an anti-thrombin action of GL and production of the reactive oxygen species (ROS; GL exerts liver protection properties by inhibiting PLA2 or by the hydroxyl radical trapping action, leading to the lowering of serum alanine and aspartate transaminase levels. The present study was undertaken to examine the possible mechanism of anti-inflammatory properties GL on IL-1beta and TNF-alpha signalling pathways in bovine fibroblast-like synoviocyte ex-vivo, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Our results clearly showed that treatment of bovine fibroblast-like synoviocyte with GL suppressed LPS-induced cell migration and invasion. Furthermore, it revealed that GL inhibited the transcription activity of MMP-9 by suppressing the binding activity of NF-κB in the MM-9 promoter. MMP-9 is an important ECM-degrading enzyme and overexpression of MMPs in important of RA-FLSs. LPS can stimulate bovine FLS to secret MMPs, and this induction is regulated at the transcription and translational levels. In this study, LPS treatment of bovine FLS caused an increase in MMP-2 and MMP-9 levels. The increase in MMP-9 expression and secretion was inhibited by ex- vitro. Furthermore, these effects were mimicked by MMP-9 siRNA. These result therefore indicate the the inhibition of LPS-induced bovine FLS invasion by GL occurs primarily by inhibiting MMP-9 expression and activity. Next we analyzed the functional significance of NF-κB transcription of MMP-9 activation in Bovine FLSs. Results from EMSA showed that GL suppressed LPS-induced NF-κB binding to the MMP-9 promotor, as NF-κB regulates transcriptional activation of multiple inflammatory cytokines, we predicted that GL might target NF-κB to suppress MMP-9 transcription by LPS. Myeloid differentiation-factor 88 (MyD88) and TIR-domain containing adaptor protein (TIRAP) are critical proteins in the LPS-induced NF-κB and apoptotic signaling pathways, GL inhibited the expression of TLR4 and MYD88. These results demonstrated that GL suppress LPS-induced MMP-9 expression through the inhibition of the induced TLR4/NFκB signaling pathway. Taken together, our results provide evidence that GL exerts anti-inflammatory effects by inhibition LPS-induced bovine FLSs migration and invasion, and the mechanisms may involve the suppression of TLR4/NFκB –mediated MMP-9 expression. Although further work is needed to clarify the complicated mechanism of GL-induced anti-invasion of bovine FLSs, GL might be used as a further anti-invasion drug with therapeutic efficacy in the treatment of immune-mediated inflammatory disease such as RA.Keywords: glycyrrhizic acid, bovine fibroblast-like synoviocyte, tlr4/nf-κb, metalloproteinase-9
Procedia PDF Downloads 3912384 Predicting of Hydrate Deposition in Loading and Offloading Flowlines of Marine CNG Systems
Authors: Esam I. Jassim
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The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography
Procedia PDF Downloads 4872383 Impact of α-Adrenoceptor Antagonists on Biochemical Relapse in Men Undergoing Radiotherapy for Localised Prostate Cancer
Authors: Briohny H. Spencer, Russ Chess-Williams, Catherine McDermott, Shailendra Anoopkumar-Dukie, David Christie
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Background: Prostate cancer is the second most common cancer diagnosed in men worldwide and the most prevalent in Australian men. In 2015, it was estimated that approximately 18,000 new cases of prostate cancer were diagnosed in Australia. Currently, for localised disease, androgen depravation therapy (ADT) and radiotherapy are a major part of the curative management of prostate cancer. ADT acts to reduce the levels of circulating androgens, primarily testosterone and the locally produced androgen, dihydrotestosterone (DHT), or by preventing the subsequent activation of the androgen receptor. Thus, the growth of the cancerous cells can be reduced or ceased. Radiation techniques such as brachytherapy (radiation delivered directly to the prostate by transperineal implant) or external beam radiation therapy (exposure to a sufficient dose of radiation aimed at eradicating malignant cells) are also common techniques used in the treatment of this condition. Radiotherapy (RT) has significant limitations, including reduced effectiveness in treating malignant cells present in hypoxic microenvironments leading to radio-resistance and poor clinical outcomes and also the significant side effects for the patients. Alpha1-adrenoceptor antagonists are used for many prostate cancer patients to control lower urinary tract symptoms, due to the progression of the disease itself or may arise as an adverse effect of the radiotherapy treatment. In Australia, a significant number (not a majority) of patients receive a α1-ADR antagonist and four drugs are available including prazosin, terazosin, alfuzosin and tamsulosin. There is currently limited published data on the effects of α1-ADR antagonists during radiotherapy, but it suggests these medications may improve patient outcomes by enhancing the effect of radiotherapy. Aim: To determine the impact of α1-ADR antagonists treatments on time to biochemical relapse following radiotherapy. Methods: A retrospective study of male patients receiving radiotherapy for biopsy-proven localised prostate cancer was undertaken to compare cancer outcomes for drug-naïve patients and those receiving α1-ADR antagonist treatments. Ethical approval for the collection of data at Genesis CancerCare QLD was obtained and biochemical relapse (defined by a PSA rise of >2ng/mL above the nadir) was recorded in months. Rates of biochemical relapse, prostate specific antigen doubling time (PSADT) and Kaplan-Meier survival curves were also compared. Treatment groups were those receiving α1-ADR antagonists treatment before or concurrent with their radiotherapy. Data was statistically analysed using One-way ANOVA and results expressed as mean ± standard deviation. Major findings: The mean time to biochemical relapse for tamsulosin, prazosin, alfuzosin and controls were 45.3±17.4 (n=36), 41.5±19.6 (n=11), 29.3±6.02 (n=6) and 36.5±17.6 (n=16) months respectively. Tamsulosin, prazosin but not alfuzosin delayed time to biochemical relapse although the differences were not statistically significant. Conclusion: Preliminary data for the prior and/or concurrent use of tamsulosin and prazosin showed a positive trend in delaying time to biochemical relapse although no statistical significance was shown. Larger clinical studies are indicated and with thousands of patient records yet to be analysed, it may determine if there is a significant effect of these drugs on control of prostate cancer.Keywords: alpha1-adrenoceptor antagonists, biochemical relapse, prostate cancer, radiotherapy
Procedia PDF Downloads 3742382 Viscoelastic Separation and Concentration of Candida Using a Low Aspect Ratio Microchannel
Authors: Seonggil Kim, Jeonghun Nam, Chae Seung Lim
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Rapid diagnosis of fungal infections is critical for rapid antifungal therapy. However, it is difficult to detect extremely low concentration fungi in blood sample. To address the limitation, separation and concentration of fungi in blood sample are required to enhance the sensitivity of PCR analysis. In this study, we demonstrated a sheathless separation and concentration of fungi, candida cells using a viscoelastic fluid. To validate the performance of the device, microparticle mixture (2 and 13 μm) was used, and those particles were successfully separated based on the size difference at high flow rate of 100 μl/min. For the final application, successful separation of the Candida cells from the white blood cells (WBCs) was achieved. Based on the viscoelastic lateral migration toward the equilibrium position, Candida cells were separated and concentrated by center focusing, while WBCs were removed by patterning into two streams between the channel center and the sidewalls. By flow cytometric analysis, the separation efficiency and the purity were evaluated as ~99% and ~ 97%, respectively. From the results, the device can be the powerful tool for detecting extremely rare disease-related cells.Keywords: candida cells, concentration, separation, viscoelastic fluid
Procedia PDF Downloads 1982381 Developing an Out-of-Distribution Generalization Model Selection Framework through Impurity and Randomness Measurements and a Bias Index
Authors: Todd Zhou, Mikhail Yurochkin
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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index
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