Search results for: disease cluster
2174 Data-Driven Crop Advisory – A Use Case on Grapes
Authors: Shailaja Grover, Purvi Tiwari, Vigneshwaran S. R., U. Dinesh Kumar
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In India, grapes are one of the most important horticulture crops. Grapes are most vulnerable to downy mildew, which is one of the most devasting diseases. In the absence of a precise weather-based advisory system, farmers spray pesticides on their crops extensively. There are two main challenges associated with using these pesticides. Firstly, most of these sprays were panic sprays, which could have been avoided. Second, farmers use more expensive "Preventive and Eradicate" chemicals than "Systemic, Curative and Anti-sporulate" chemicals. When these chemicals are used indiscriminately, they can enter the fruit and cause health problems such as cancer. This paper utilizes decision trees and predictive modeling techniques to provide grape farmers with customized advice on grape disease management. This model is expected to reduce the overall use of chemicals by approximately 50% and the cost by around 70%. Most of the grapes produced will have relatively low residue levels of pesticides, i.e., below the permissible level.Keywords: analytics in agriculture, downy mildew, weather based advisory, decision tree, predictive modelling
Procedia PDF Downloads 742173 Estimating Housing Prices Using Automatic Linear Modeling in the Metropolis of Mashhad, Iran
Authors: Mohammad Rahim Rahnama
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Market-transaction price for housing is the main criteria for determining municipality taxes and is determined and announced on an annual basis. Of course, there is a discrepancy between the actual value of transactions in the Bureau of Finance (P for short) or municipality (P´ for short) and the real price on the market (P˝). The present research aims to determine the real price of housing in the metropolis of Mashhad and to pinpoint the price gap with those of the aforementioned apparatuses and identify the factors affecting it. In order to reach this practical objective, Automatic Linear Modeling, which calls for an explanatory research, was utilized. The population of the research consisted of all the residential units in Mashhad, from which 317 residential units were randomly selected. Through cluster sampling, out of the 170 income blocks defined by the municipality, three blocks form high-income (Kosar), middle-income (Elahieh), and low-income (Seyyedi) strata were surveyed using questionnaires during February and March of 2015 and the information regarding the price and specifications of residential units were gathered. In order to estimate the effect of various factors on the price, the relationship between independent variables (8 variables) and the dependent variable of the housing price was calculated using Automatic Linear Modeling in SPSS. The results revealed that the average for housing price index is 788$ per square meter, compared to the Bureau of Finance’s prices which is 10$ and that of municipality’s which is 378$. Correlation coefficient among dependent and independent variables was calculated to be R²=0.81. Out of the eight initial variables, three were omitted. The most influential factor affecting the housing prices is the quality of Quality of construction (Ordinary, Full, Luxury). The least important factor influencing the housing prices is the variable of number of sides. The price gap between low-income (Seyyedi) and middle-income (Elahieh) districts was not confirmed via One-Way ANOVA but their gap with the high-income district (Kosar) was confirmed. It is suggested that city be divided into two low-income and high-income sections, as opposed three, in terms of housing prices.Keywords: automatic linear modeling, housing prices, Mashhad, Iran
Procedia PDF Downloads 2552172 We Have Never Seen a Dermatologist. Reaching the Unreachable Through Teledermatology
Authors: Innocent Atuhe, Babra Nalwadda, Grace Mulyowa Kitunzi, Annabella Haninka Ejiri
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Background: Atopic Dermatitis (AD) is one of the most prevalent and growing chronic inflammatory skin diseases in African prisons. AD care is limited in African due to lack of information about the disease amongst primary care workers, limited access to dermatologists, lack of proper training of healthcare workers, and shortage of appropriate treatments. We designed and implemented the Prisons Telederma project based on the recommendations of the International Society of Atopic Dermatitis. Our overall goal was to increase access to dermatologist-led care for prisoners with AD through teledermatology in Uganda. We aimed to; i) to increase awareness and understanding of teledermatology among prison health workers; and ii) to improve treatment outcomes of prisoners with atopic dermatitis through increased access to and utilization of consultant dermatologists through teledermatology in Uganda prisons: Approach: We used Store-and-forward Teledermatology (SAF-TD) to increase access to dermatologist-led care for prisoners and prisons staff with AD. We conducted a five days training for prison health workers using an adapted WHO training guide on recognizing neglected tropical diseases through changes on the skin together with an adapted American Academy of Dermatology (AAD) Childhood AD Basic Dermatology Curriculum designed to help trainees develop a clinical approach to the evaluation and initial management of patients with AD. This training was followed by blended e-learning, webinars facilitated by consultant Dermatologists with local knowledge of medication and local practices, apps adjusted for pigmented skin, WhatsApp group discussions, and sharing pigmented skin AD pictures and treatment via zoom meetings. We hired a team of Ugandan Senior Consultant dermatologists to draft an iconographic atlas of the main dermatoses in pigmented African skin and shared this atlas with prison health staff for use as a job aid. We had planned to use MySkinSelfie mobile phone application to take and share skin pictures of prisoners with AD with Consultant Dermatologists, who would review the pictures and prescribe appropriate treatment. Unfortunately, the National Health Service withdrew the app from the market due to technical issues. We monitored and evaluated treatment outcomes using the Patient Oriented Eczema Measure (POEM) tool. We held four advocacy meetings to persuade relevant stakeholders to increase supplies and availability of first-line AD treatments such as emollients in prison health facilities. Results: Draft iconographic atlas of the main dermatoses in pigmented African skin Increased proportion of prison health staff with adequate knowledge of AD and teledermatology from 20% to 80% Increased proportion of prisoners with AD reporting improvement in disease severity (POEM scores) from 25% to 35% in one year. Increased proportion of prisoners with AD seen by consultant dermatologist through teledermatology from 0% to 20% in one year. Increased the availability of AD recommended treatments in prisons health facilities from 5% to 10% in one yearKeywords: teledermatology, prisoners, reaching, un-reachable
Procedia PDF Downloads 1162171 The Comparison between bFGF and Small Molecules in Derivation of Chicken Primordial Germ Cells and Embryonic Germ Cells
Authors: Maryam Farzaneh, Seyyedeh Nafiseh Hassani, Hossein Baharvand
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Objective: Chicken gonadal tissue has a two population such primordial germ cells (PGCs) and stromal cells (somatic cells). PGCs and embryonic germ cells (EGCs) that is a pluripotent type of PGCs in long-term culture are suitable sources for the production of chicken pluripotent stem cell lines, transgenic birds, vaccine and recombinant protein production. In general, the effect of growth factors such bFGF and mouse LIF on derivation of PGCs in vitro are important and in this study we could see the unique effect of small molecules such PD032 and SB43 as a chemical, in comparison to growth factors. Materials and Methods: After incubation of fertilized chicken egg up to 6 days and isolation of primary gonadal tissues and culture of mixed cells like PGCs and stromal cells. PGCs proliferate in the present of fetal calf serum (FCS) and small molecules and in another group bFGF, that these factors are important for PGCs culture and derivation. Somatic cells produce a multilayer feeder under the PGCs in primary culture and PGCs make a small cluster under these cells. Results: In present of small molecules and high volume of FCS (15%), the present of EGCs as a pluripotent stem cells were clear four weeks, that they had a positive immune-staining and periodic acid-Schiff staining (PAS), but in present of growth factors like bFGF without any chemicals, the present of PGCs were clear but after 7 until 10 days, there were disappear. Conclusion: Until now we have seen many researches about derivation and maintenance of chicken PGCs, in the hope of understanding the mechanisms that occur during germline development and production of a therapeutic product by transgenic birds. There are still many unknowns in this area and this project will try to have efficient conditions for identification of suitable culture medium for long-term culture of PGCs in vitro without serum and feeder cells.Keywords: chicken gonadal primordial germ cells, pluripotent stem cells, growth factors, small molecules, transgenic birds
Procedia PDF Downloads 4342170 Production and Quality Control of a Novel 153Sm-Complex for Radiotherapy of Bone-Metastases
Authors: H. Yousefnia, R. Enayati, M. Hosntalab, S. Zolghadri, A. Bahrami-Samani
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Bone metastases occur in many cases at an early stage of the tumour disease, however their symptoms are recognized rather late. The aim of this study was the preparation of 153Sm-(4-{[bis-(phosphonomethyl))carbamoyl]methyl}-7,10-bis(carboxymethyl) 1,4,7,10-tetraazacyclododec-1-yl) acetic acid (BPAMD) for bone pain palliation therapy. 153Sm was produced at Tehran research reactor via 152Sm(n,γ)153Sm reaction. 200 µl of 1mg/ml BPAMD solution was added to the vial containing 1 mCi 153Sm and the mixture was heated up to 90 0C for 1 h. The radiochemical purity of the complex was measured by ITLC method. The final solution with radiochemical purity of more than 95% was injected to BALB mice and bio distribution was determined up to 48 h. SPECT images were acquired after 2 and 24 h post injection. While high bone uptake was confirmed by both the bio distribution studies and SPECT imaging, accumulation in other organs was approximately negligible. The results show that 153Sm-BPAMD can be used as an excellent tracer for bone pain palliation therapy.Keywords: bone metastases, BPAMD, 153Sm, radiotherapy
Procedia PDF Downloads 5972169 D-Care: Diabetes Care Application to Enhance Diabetic Awareness to Diabetes in Indonesia
Authors: Samara R. Dania, Maulana S. Aji, Dewi Lestari
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Diabetes is a common disease in Indonesia. One of the risk factors of diabetes is an unhealthy diet which is consuming food that contains too much glucose, one of glucose sources presents in food containing carbohydrate. The purpose of this study is to identify the amount of glucose level in the consumed food. The authors use literature studies for this research method. For the results of this study, the authors expect diabetics to be more aware of diabetes by applying daily dietary regulation through D-Care. D-Care is an application that can enhance people awareness to diabetes in Indonesia. D-Care provides two menus; there are nutrition calculation and healthy food. Nutrition calculation menu is used for knowing estimated glucose intake level by calculating food that consumed each day. Whereas healthy food menu, it provides a combination of healthy food menu for diabetic. The conclusion is D-Care is useful to be used for reducing diabetes prevalence in Indonesia.Keywords: D-Care, diabetes, awareness, healthy food
Procedia PDF Downloads 4192168 A Portable Device for Pulse Wave Velocity Measurements
Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen
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Pulse wave velocity (PWV) of blood flow provides important information of vessel property and blood pressure which can be used to assess cardiovascular disease. However, the above measurements need expensive equipment, such as Doppler ultrasound, MRI, angiography etc. The photoplethysmograph (PPG) signals are commonly utilized to detect blood volume changes. In this study, two infrared (IR) probes are designed and placed at a fixed distance from finger base and fingertip. An analog circuit with automatic gain adjustment is implemented to get the stable original PPG signals from above two IR probes. In order to obtain the time delay precisely between two PPG signals, we obtain the pulse transit time from the second derivative of the original PPG signals. To get a portable, wireless and low power consumption PWV measurement device, the low energy Bluetooth 4.0 (BLE) and the microprocessor (Cortex™-M3) are used in this study. The PWV is highly correlated with blood pressure. This portable device has potential to be used for continuous blood pressure monitoring.Keywords: pulse wave velocity, photoplethysmography, portable device, biomedical engineering
Procedia PDF Downloads 5272167 Variation in Maternal Mortality in Sidama National Regional State, Southern Ethiopia: A Population Based Cross Sectional Household Survey
Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker
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Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia
Procedia PDF Downloads 722166 Bioengineering System for Prediction and Early Prenosological Diagnostics of Stomach Diseases Based on Energy Characteristics of Bioactive Points with Fuzzy Logic
Authors: Mahdi Alshamasin, Riad Al-Kasasbeh, Nikolay Korenevskiy
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We apply mathematical models for the interaction of the internal and biologically active points of meridian structures. Amongst the diseases for which reflex diagnostics are effective are those of the stomach disease. It is shown that use of fuzzy logic decision-making yields good results for the prediction and early diagnosis of gastrointestinal tract diseases, depending on the reaction energy of biologically active points (acupuncture points). It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained by using fuzzy logic decision-making.Keywords: acupuncture points, fuzzy logic, diagnostically important points (DIP), confidence factors, membership functions, stomach diseases
Procedia PDF Downloads 4672165 Hydrogen, a Novel Therapeutic Molecule, in Osteosarcoma Disease
Authors: Priyanka Sharma, Rajeshwar Nath Srivastava
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Hydrogen has a high level of efficacy in suppressing tumour growth. The role of hydrogen in cancer treatment is unclear. This groundbreaking research will focus on the most effective therapeutic approach for osteosarcoma. Recent data reveals that hydrogen, a naturally occurring gaseous chemical, can protect cells from death. However, little is known about the signalling pathways that regulate cardiac cell death and individual apoptosis signalling by H2 and its downstream targets. According to certain research, the anti-tumor effect of H2 released by magnesium-based biomaterials is mediated by the P53-mediated lysosome-mitochondria apoptosis signalling pathway, bolstering the biomaterial's therapeutic potential as a localised anti-tumor treatment. The role of the H2 molecule in the signalling of apoptotic, autophagic, necroptotic, and pyroptotic cell death in Osteosarcoma is discussed in this paper. Potential Hydrogen-based therapy techniques will broaden the treatment horizon for Osteosarcoma.Keywords: osteosarcoma, metastasis, hhydrogen, therapeutic
Procedia PDF Downloads 1392164 Semi-Automatic Design and Fabrication of Water Waste Cleaning Machine
Authors: Chanida Tangjai Benchalak Muangmeesri, Dechrit Maneetham
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Collection of marine garbage in the modern world, where technology is vital to existence. Consequently, technology can assist in reducing the duplicate labor in the subject of collecting trash in the water that must be done the same way repeatedly owing to the consequence of suffering an emerging disease or COVID-19. This is due to the rapid advancement of technology. As a result, solid trash and plastic garbage are increasing. Agricultural gardens, canals, ponds, and water basins are all sources of water. Building boat-like instruments for rubbish collection in the water will be done this time. It has two control options, boat control via remote control and boat control via an Internet of Things system. A solar panel with a power output of 40 watts powers the system being able to store so accurate and precise waste collection, allowing for thorough water cleaning. The primary goals are to keep the water's surface clean and assess its quality to support the aquatic ecology.Keywords: automatic boat, water treatment, cleaning machine, iot
Procedia PDF Downloads 912163 Use of Cassava Flour in Cakes Processing
Authors: S. S. Silva, S. M. A. Souza, C. F. P. Oliveira
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Brazil's agriculture is a major economic base in the country; in addition, family farming is directly responsible for the production of most agricultural products in Brazil, such as cassava. The number of studies on the use of cassava and its derivatives in the food industry has been increased, which is the basis of this study. Sought to develop a food that take advantage the products from farmers, adding value to these products and to study its effects as a replacement for wheat flour. For such elaborated a gluten-free cake – aiming to meet the needs of the celiac public – containing cassava flour, cane sugar, honey, egg, soya oil, coconut desiccated, baking powder and water. For evaluation of their characteristics technological, physicochemical and texture characterizations were done. Cake showed similar characteristics of cake made with wheat flour and growth and aeration of the dough. In sum up, marketing the product is viable, in that it has a typical overall appearance of cake made of wheat flour, meet the needs of celiac people and value the family farming.Keywords: baking, cake, cassava flour, celiac disease
Procedia PDF Downloads 4252162 Use of Multivariate Statistical Techniques for Water Quality Monitoring Network Assessment, Case of Study: Jequetepeque River Basin
Authors: Jose Flores, Nadia Gamboa
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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.Keywords: PCA, HCA, Jequetepeque, multivariate statistical
Procedia PDF Downloads 3552161 Effects of an Online Positive Psychology Program on Stress, Depression, and Anxiety Symptoms of Emerging Adults
Authors: Gabriela R. Silveira, Claudia S. Rocha, Lais S. Vitti, Jeane L. Borges, Helen B. Durgante
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Emerging adulthood occurs after adolescence in a period that maybe be marked by experimentation, identity reconfigurations, labor life demands, and insertion in the work environment, which tends to generate stress and emotional instability. Health promotion programs for the development of strengths and virtues, based on Positive Psychology, for emerging adults are sparse in Brazil. The aim of this study was to evaluate the preliminary effects of an online multi-component Positive Psychology program for the health promotion of emerging adults based on Cognitive Behavioural Therapy and Positive Psychology. The program included six online (synchronous) weekly group sessions of approximately two hours each and homework (asynchronous) activities. The themes worked were Values and self-care/Prudence, Optimism, Empathy, Gratitude, Forgiveness, and Meaning of life and work. This study presents data from a longitudinal, pre-experimental design with pre (T1) and post-test (T2) evaluation in the intervention group. 47 individuals aged between 19-30 years old participated, mean age of 24.53 years (SD=3.13), 37 females (78.7%). 42 (89.4%) self-defined as heterosexual, four (8.5%) as homosexual, and one (2.5%) as bisexual. 33 (70.2%) had incomplete higher education, four (8.5%) completed higher education, and seven (14.9%) had a graduate level of education. 27 participants worked (57.4%), out of which 25 were health workers (53.2%). 14 (29.8%) were caregivers, 27 (57.4%) had a spiritual belief, 36 (76.6%) had access to leisure, and 38 (80.9%) had perceived social support. The instruments used were a sociodemographic questionnaire, the 10-item Perceived Stress Scale, and the 12-item General Health Questionnaire. The program was advertised on social networks and interested participants filled out the Consent Form and the evaluation protocol at T1 and T2 via Google Docs form. The main research was approved (CEP n.1,899,368; 4,143,219; CAAE: 61997516.5.0000.5334) and complied with sanitary and Ethics criteria in research with human beings. Wilcoxon statistics revealed significant improvements in indicators of perceived stress between T1 (X=22.21, SD=6.79) and T2 (X=15.10, SD=5.82); (Z=-4.353; p=0.001) as well as depression and anxiety symptoms (T1:X=26.72, SD=8.84; T2: X=19.23, SD=4.68); (Z=-3.945, p=0.001) of the emerging adults after their participation in the programme. The programme has an innovative character not only for presenting an online Positive Psychology approach but also for being based on an intervention developed, evaluated, and manualized in Brazil. By focusing on emerging adults, this study contributes to advancing research on a relatively new field in developmental studies. As a limitation, this is a pre-experimental and pilot study, requiring an increase in sample size for greater statistical robustness, also qualitative data analysis is crucial for methodological complementarity. The importance of investing efforts to accompany this age group and provide advances in longitudinal research in the area of health promotion and disease prevention is highlighted.Keywords: emerging adults, disease prevention, health promotion, online program
Procedia PDF Downloads 1032160 A Data-Driven Platform for Studying the Liquid Plug Splitting Ratio
Authors: Ehsan Atefi, Michael Grigware
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Respiratory failure secondary to surfactant deficiency resulting from respiratory distress syndrome is considered one major cause of morbidity in preterm infants. Surfactant replacement treatment (SRT) is considered an effective treatment for this disease. Here, we introduce an AI-mediated approach for estimating the distribution of surfactant in the lung airway of a newborn infant during SRT. Our approach implements machine learning to precisely estimate the splitting ratio of a liquid drop during bifurcation at different injection velocities and patient orientations. This technique can be used to calculate the surfactant residue remaining on the airway wall during the surfactant injection process. Our model works by minimizing the pressure drop difference between the two airway branches at each generation, subject to mass and momentum conservation. Our platform can be used to generate feedback for immediately adjusting the velocity of injection and patient orientation during SRT.Keywords: respiratory failure, surfactant deficiency, surfactant replacement, machine learning
Procedia PDF Downloads 1262159 Unsupervised Part-of-Speech Tagging for Amharic Using K-Means Clustering
Authors: Zelalem Fantahun
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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.Keywords: POS tagging, Amharic, unsupervised learning, k-means
Procedia PDF Downloads 4512158 Analysis of Ancient Bone DNA Samples From Excavations at St Peter’s Burial Ground, Blackburn
Authors: Shakhawan K. Mawlood, Catriona Pickard, Benjamin Pickard
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In summer 2015 the remains of 800 children are among 1,967 bodies were exhumed by archaeologists at St Peter's Burial Ground in Blackburn, Lancashire. One hundred samples from these 19th century ancient bones were selected for DNA analysis. These comprised samples biased for those which prior osteological evidence indicated a potential for microbial infection by Mycobacterium tuberculosis (causing tuberculosis, TB) or Treponema pallidum (causing Syphilis) species, as well a random selection of other bones for which visual inspection suggested good preservation (and, therefore, likely DNA retrieval).They were subject to polymerase chain reaction (PCR) assays aimed at detecting traces of DNA from infecting mycobacteria, with the purpose both of confirming the palaeopathological diagnosis of tuberculosis and determining in individual cases whether disease and death was due to M. tuberculosis or other reasons. Our secondary goal was to determine sex determination and age prediction. The results demonstrated that extraction of vast majority ancient bones DNA samples succeeded.Keywords: ancient bone, DNA, tuberculosis, age prediction
Procedia PDF Downloads 1032157 Mosquito Repellent Finishing of Cotton Using Pepper Tree (Schinus molle) Seed Oil Extract
Authors: Granch Berhe Tseghai, Tekalgn Gebremedhin Belay, Abrehaley Hagos Gebremariam
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Mosquito repellent textiles are one of the most growing ways to advance the textile field by providing the needed characteristics of protecting against mosquitoes, especially in the tropical areas. These types of textiles ensure the protection of human beings from the mosquitoes and the mosquito-borne disease includes malaria, filariasis and dengue fever. In this work Schinus Molle oil (pepper tree oil) was used for mosquito repellent finish as a preformatted thing. This study focused on the penetration of mosquito repellent finish in textile applications as well as nature based alternatives to commercial chemical mosquito repellents in the market. Suitable techniques and materials to achieve mosquito repellency are discussed and pointed out according to our project. In this study textile, sample was treated with binder and schinus oil. The different property has been studied for effective mosquito repellency.Keywords: cotton, Schinus molle seed oil, mosquito repellent, mosquito-borne diseases
Procedia PDF Downloads 2852156 The Many Faces of Cancer and Knowing When to Say Stop
Authors: Diwei Lin, Amanda Jh. Tan
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We present a very rare case of de novo large cell neuroendocrine carcinoma of the prostate (LCNEC) in an 84-year-old male on a background of high-grade, muscle-invasive transitional cell carcinoma of the bladder. While NE tumours account for 1% to 5% of all cases of prostate cancer and scattered NE cells can be found in 10% to 100% of prostate adenocarcinomas, pure LCNEC of the prostate is extremely rare. Most LCNEC of the prostate is thought to originate by clonal progression under the selection pressure of therapy and refractory to long-term hormonal treatment for adenocarcinoma of the prostate. De novo LCNEC is only described in case reports and is thought to develop via direct malignant transformation. Limited data in the English literature makes it difficult to accurately predict the prognosis of LCNEC of the prostate. However, current evidence suggesting that increasing NE differentiation in prostate adenocarcinoma is associated with a higher stage, high-grade disease, and a worse prognosis.Keywords: large cell neuroendocrine cancer, prostate cancer, refractory cancer, medical and health sciences
Procedia PDF Downloads 4222155 COVID-19: Potential Effects of Nutritional Factors on Inflammation Relief
Authors: Maryam Nazari
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COVID-19 is a respiratory disease triggered by the novel coronavirus, SARS-CoV-2, that has reached pandemic status today. Acute inflammation and immune cells infiltration into lung injuries result in multi-organ failure. The presence of other non-communicable diseases (NCDs) with systemic inflammation derived from COVID-19 may exacerbate the patient's situation and increase the risk for adverse effects and mortality. This pandemic is a novel situation and the scientific community at this time is looking for vaccines or drugs to treat the pathology. One of the biggest challenges is focused on reducing inflammation without compromising the correct immune response of the patient. In this regard, addressing the nutritional factors should not be overlooked not only as a matter of avoiding the presence of NCDs with severe infections but also as an adjunctive way to modulate the inflammatory status of the patients. Despite the pivotal role of nutrition in modifying immune response, due to the novelty of the COVID-19 disease, information about the effects of specific dietary agents is limited in this area. From the macronutrients point of view, protein deficiency (quantity or quality) has negative effects on the number of functional immunoglobulins and gut-associated lymphoid tissue (GALT). High biological value proteins or some amino acids like arginine and glutamine are well known for their ability to augment the immune system. Among lipids, fish oil has the ability to inactivate enveloped viruses, suppress pro-inflammatory prostaglandin production and block platelet-activating factors and their receptors. In addition, protectin D1, which is an Omega-3 PUFAs derivation, is a novel antiviral drug. So it seems that these fatty acids can reduce the severity and/or improve recovery of patients with COVID-19. Carbohydrates with lower glycemic index and fibers are associated with lower levels of inflammatory cytokines (CRP, TNF-α, and IL-6). Short-Chain Fatty acids not only exert a direct anti-inflammatory effect but also provide appropriate gut microbial, which is important in gastrointestinal issues related to COVID-19. From the micronutrients point of view, Vitamins A, C, D, E, iron, magnesium, zinc, selenium and copper play a vital role in the maintenance of immune function. Inadequate status in these nutrients may result in decreased resistance against COVID-19 infection. There are specific bioactive compounds in the diet that interact with the ACE2 receptor, which is the gateway for SARS and SARS-CoV-2, and thus controls the viral infection. Regarding this, the potential benefits of probiotics, resveratrol (a polyphenol found in grape), oleoylethanolamide (derived from oleic acid), and natural peroxisome proliferator-activated receptor γ agonists in foodstuffs (like curcumin, pomegranate, hot pepper) are suggested. Yet, it should be pointed out that most of these results have been reported in animal models and further human studies are needed to be verified.Keywords: Covid-19, inflammation, nutrition, dietary agents
Procedia PDF Downloads 1742154 The Relationship between Amplitude and Stability of Circadian Rhythm with Sleep Quality and Sleepiness: A Population Study, Kerman 2018
Authors: Akram Sadat Jafari Roodbandi, Farzaneh Akbari, Vafa Feyzi, Zahra Zare, Zohreh Foroozanfar
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Introduction: Circadian rhythm or sleep-awake cycle in 24 hours is one of the important factors affecting the physiological and psychological characteristics in humans that contribute to biochemical, physiological and behavioral processes and helps people to set up brain and body for sleep or active awakening during certain hours. The purpose of this study was to investigate the relationship between the characteristics of circadian rhythms on the sleep quality and sleepiness according to their demographic characteristics such as age. Methods: This cross-sectional descriptive-analytic study was carried out among the general population of Kerman, aged 15-84 years. After dividing the age groups into 10-year demographic characteristics questionnaire, the type of circadian questionnaire, Pittsburgh sleep quality questionnaire and Euporth sleepiness questionnaire were completed in equal numbers between men and women of that age group. Using cluster sampling with effect design equal 2, 1300 questionnaires were distributed during the various hours of 24 hours in public places in Kerman city. Data analysis was done using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: In this study, 1147 subjects were included in the study, 584 (50.9%) were male and the rest were women. The mean age was 39.50 ± 15.38. 133 (11.60%) subjects from the study participants had sleepiness and 308 (26.90%) subjects had undesirable sleep quality. Using linear regression test, sleep quality was the significant correlation with sex, hours needed for sleep at 24 hours, chronic illness, sleepiness, and circadian rhythm amplitude. Sleepiness was the meaningful relationship with marital status, sleep-wake schedule of other family members and the stability of circadian rhythm. Both women and men, with age, decrease the quality of sleep and increase the rate of sleepiness. Conclusion: Age, sex, and type of circadian people, the need for sleep at 24 hours, marital status, sleep-wake schedule of other family members are significant factors related to the sleep quality and sleepiness and their adaptation to night shift work.Keywords: circadian type, sleep quality, sleepiness, age, shift work
Procedia PDF Downloads 1532153 Artificial Neural Network Based Model for Detecting Attacks in Smart Grid Cloud
Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal
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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid
Procedia PDF Downloads 3182152 Long-Term Psychosocial Issues Among COVID-19 Survivors in Kathmandu Valley
Authors: Nabin Prasad Joshi, Samiksha Neupane
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Since its emergence in December 2019, Corona Virus disease has impacted several countries, affecting many people. The first cases were recorded in Wuhan, China, between December 2019 and January 2020. Italy is one of the affected countries in Europe. The relations between India and Nepal have reverted to the pre-pandemic period as both countries have open borders. The study focused on the overall psychosocial impact among covid-19 survivors in their life what are the changes they are facing after covid also how are their relations with friends and relatives after they have covid in different municipalities of Kathmandu valley, where people from different regions are living in rent and have their own houses. Support from friends and family during a pandemic can prevent it if it is strong enough. Nonetheless, there were risk factors for psychosocial damage, including a lack of or insufficient family and social support, psychiatric assistance, and inadequate insurance or compensation. Poorer mental health outcomes were inversely correlated with social rejection or isolation.Keywords: stress, anxiety, depression, Kathmandu
Procedia PDF Downloads 1022151 Influence of HIV Testing on Knowledge of HIV/AIDS Prevention Practices and Transmission among Undergraduate Youths in North-West University, Mafikeng
Authors: Paul Bigala, Samuel Oladipo, Steven Adebowale
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This study examines factors influencing knowledge of HIV/AIDS Prevention Practices and Transmission (KHAPPT) among young undergraduate students (15-24 years). Knowledge composite index was computed for 820 randomly selected students. Chi-square, ANOVA, and multinomial logistic regression were used for the analyses (α=.05). The overall mean knowledge score was 16.5±3.4 out of a possible score of 28. About 83% of the students have undergone HIV test, 21.0% have high KHAPPT, 18% said there is cure for the disease, 23% believed that asking for condom is embarrassing and 11.7% said it is safe to share unsterilized sharp objects with friends or family members. The likelihood of high KHAPPT was higher among students who have had HIV test (OR=3.314; C.I=1.787-6.145, p<0.001) even when other variables were used as control. The identified predictors of high KHAPPT were; ever had HIV test, faculty, and ever used any HIV/AIDS prevention services. North-West University Mafikeng should intensify efforts on the HIV/AIDS awareness program on the campus.Keywords: HIV/AIDS knowledge, undergraduate students, HIV testing, Mafikeng
Procedia PDF Downloads 4432150 Two-Level Separation of High Air Conditioner Consumers and Demand Response Potential Estimation Based on Set Point Change
Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee
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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems
Procedia PDF Downloads 672149 Strategy and Coarctation of the Aorta Repair
Authors: Shirin Jalili, Ramin Ghasemi Shayan
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Coarctation of the aorta (CoA) may be a common (CHD), which is the seventh most common sort of CHD. Still, this is often likely a think little off since the determination may be deferred, indeed within the pediatric populace. The choice for surgical repair incorporates resection of the contracted section with end-to-end or end-to-side anastomosis, subclavian fold aortoplasty, resection, and join the intervention, or prosthetic fix aortoplasty. Drastically expanded end-to-end repair or switched subclavian fold aortoplasty can be utilized when the coarctation expands to the distal arch. Swell angioplasty can be a palliative choice sometime recently the conclusive redress. Its objective is to stabilize high-risk patients that cannot be submitted to quick surgical intercession, such as untimely newborns. For disconnected and discrete coarctations, it can, as a rule, be drawn nearer and repaired by means of cleared out thoracotomy, extraction of the infected aorta (coarctectomy), and remaking, ordinarily by amplified end-to-end anastomosis. In this article, we need to supply a diagram of current proposals and strategies utilized to picture coarctations of the aorta.Keywords: coarctation of the aorta, congenital heart disease, strategies, surgical repair
Procedia PDF Downloads 1642148 Empowering a New Frontier in Heart Disease Detection: Unleashing Quantum Machine Learning
Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz
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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.Keywords: quantum machine learning, SVM, QSVM, matrix product state
Procedia PDF Downloads 942147 Effectiveness of Prehabilitation on Improving Emotional and Clinical Recovery of Patients Undergoing Open Heart Surgeries
Authors: Fatma Ahmed, Heba Mostafa, Bassem Ramdan, Azza El-Soussi
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Background: World Health Organization stated that by 2020 cardiac disease will be the number one cause of death worldwide and estimates that 25 million people per year will suffer from heart disease. Cardiac surgery is considered an effective treatment for severe forms of cardiovascular diseases that cannot be treated by medical treatment or cardiac interventions. In spite of the benefits of cardiac surgery, it is considered a major stressful experience for patients who are candidate for surgery. Prehabilitation can decrease incidences of postoperative complications as it prepares patients for surgical stress through enhancing their defenses to meet the demands of surgery. When patients anticipate the postoperative sequence of events, they will prepare themselves to act certain behaviors, identify their roles and actively participate in their own recovery, therefore, anxiety levels are decreased and functional capacity is enhanced. Prehabilitation programs can comprise interventions that include physical exercise, psychological prehabilitation, nutritional optimization and risk factor modification. Physical exercises are associated with improvements in the functioning of the various physiological systems, reflected in increased functional capacity, improved cardiac and respiratory functions and make patients fit for surgical intervention. Prehabilitation programs should also prepare patients psychologically in order to cope with stress, anxiety and depression associated with postoperative pain, fatigue, limited ability to perform the usual activities of daily living through acting in a healthy manner. Notwithstanding the benefits of psychological preparations, there are limited studies which investigated the effect of psychological prehabilitation to confirm its effect on psychological, quality of life and physiological outcomes of patients who had undergone cardiac surgery. Aim of the study: The study aims to determine the effect of prehabilitation interventions on outcomes of patients undergoing cardiac surgeries. Methods: Quasi experimental study design was used to conduct this study. Sixty eligible and consenting patients were recruited and divided into two groups: control and intervention group (30 participants in each). One tool namely emotional, physiological, clinical, cognitive and functional capacity outcomes of prehabilitation intervention assessment tool was utilized to collect the data of this study. Results: Data analysis showed significant improvement in patients' emotional state, physiological and clinical outcomes (P < 0.000) with the use of prehabilitation interventions. Conclusions: Cardiac prehabilitation in the form of providing information about surgery, circulation exercise, deep breathing exercise, incentive spirometer training and nutritional education implemented daily by patients scheduled for elective open heart surgery one week before surgery have been shown to improve patients' emotional state, physiological and clinical outcomes.Keywords: emotional recovery, clinical recovery, coronary artery bypass grafting patients, prehabilitation
Procedia PDF Downloads 2042146 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach
Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini
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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 1672145 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach
Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini
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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 mechanismsKeywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing
Procedia PDF Downloads 159