Search results for: disease trajectory
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4082

Search results for: disease trajectory

3812 Digital Planet: Readying for the Rise of the E-Consumer

Authors: Bhaskar Chakravorti, Christopher Tunnard, Ravi Shankar Chaturvedi

Abstract:

This report introduces the Digital Evolution Index (DEI) as a way to gauge the transformation of economies in the advanced and developing world from traditional brick-and-mortar to digitally enabled. The DEI measures the digital trajectories of 50 countries to provide actionable, data-informed insights for businesses, investors and policymakers. Created by The Fletcher School, in collaboration with MasterCard Worldwide and DataCash, the DEI analyzes the key underlying drivers and barriers that govern a country’s evolution into a digital economy: Demand, Supply, Institutional Environment and Innovation. A longitudinal analysis of these four drivers during the years 2008 to 2013 reveals both the current state of a country’s digital economy, as well as changes over time. Combining these two measures allows us to assign each country to one of four Trajectory Zones: • Stand Out countries have shown high levels of digital development in the past and continue to remain on an upward trajectory. • Stall Out countries have achieved a high level of evolution in the past but are losing momentum and risk falling behind. • Break Out countries have the potential to develop strong digital economies. Though their overall score is still low, they are moving upward and are poised to become Stand Out countries in the future. • Watch Out countries face significant opportunities and challenges, with low scores on both current level and upward motion of their DEI. Some may be able to overcome limitations with clever innovations and stopgap measures, while others seem to be stuck.

Keywords: e-commerce, digital evolution, digital commerce ecosystems, e-consumer

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3811 Burden of Cardiovascular Diseases in Dubrovnik- Neretva County 2018-2021

Authors: Tarnai Tena, Strinić Dean

Abstract:

Chronic non-communicable diseases are today the leading cause of mortality, morbidity and mortality disability at the world level and in Croatia. Among them are the most represented precisely cardiovascular diseases (CVD), so today we are talking about their global card epidemic. From 2018 to 2021, cardiovascular diseases are the leading cause of death for both women and men in the Dubrovnik- Neretva County. With regard to the COVID-19 pandemic, which has taken over, without forgetting how much these patients are additionally affected, we are still talking about the primary cause of sickness and death in the population of this county and region. In this record, we present collected data processed according to gender and disease classification. We also bring a kind of overview because, for years, we have been following how the population of one of the origins of the Mediterranean diet has been struggling with cardiovascular diseases.

Keywords: cardiovascular disease, burden, COVID-19, epidemiology, ishemic heart disease, cardiovascular medicine

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3810 Use of External Sensory Stimuli in the Treatment of Parkinson Disease: Literature Review

Authors: Hadi O. Tohme

Abstract:

This study is a review on the effectiveness of new physiotherapy techniques with external sensory stimulus compared to standard physiotherapy in the daily activities of patients with Parkinson's disease. Twenty studies from 1996 to 2015 were analyzed and discussed in this review, using the rehabilitation strategy with external sensory stimulus evaluating walking, freezing episodes, balance, transfers, and daily activities of parkinsonian patients. The study highlights the effectiveness of the variety of rehabilitation with cueing strategy used in the treatment of Parkinson's disease. Based on the literature review completed, there is a need for more specific trials with better treatment strategies to support the most appropriate choice of physiotherapy intervention using external sensory stimulus to the type and frequency of this stimulus. In addition, no trials examined the long-term benefits of the physiotherapy intervention with the external sensory stimulus. In order to determine if, or how long the improvements due to the external sensory stimulus physiotherapy intervention can last, long-term follow-up should be performed.

Keywords: cueing strategy, external sensory stimulus, parkinson disease, rehabilitation for parkinson, sensory attention focused exercises, sensory strategy reeducation

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3809 Traffic Prediction with Raw Data Utilization and Context Building

Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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3808 AniMoveMineR: Animal Behavior Exploratory Analysis Using Association Rules Mining

Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

Abstract:

Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

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3807 Prediction of Alzheimer's Disease Based on Blood Biomarkers and Machine Learning Algorithms

Authors: Man-Yun Liu, Emily Chia-Yu Su

Abstract:

Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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3806 Rhizosphere Microbiome Involvement in the Natural Suppression of Soybean Cyst Nematode in Disease Suppressive Soil

Authors: M. Imran Hamid, Muzammil Hussain, Yunpeng Wu, Meichun Xiang, Xingzhong Liu

Abstract:

The rhizosphere microbiome elucidate multiple functioning in the soil suppressiveness against plant pathogens. Soybean rhizosphere microbial communities may involve in the natural suppression of soybean cyst nematode (SCN) populations in disease suppressive soils. To explore these ecological mechanisms of microbes, a long term monoculture suppressive soil were taken into account for further investigation to test the disease suppressive ability by using different treatments. The designed treatments are as, i) suppressive soil (S), ii) conducive soil (C), iii) conducive soil mixed with 10% (w/w) suppressive soil (CS), iv) suppressive soil treated at 80°C for 1 hr (S80), and v) suppressive soil treated with formalin (SF). By using an ultra-high-throughput sequencing approach, we identified the key bacterial and fungal taxa involved in SCN suppression. The Phylum-level investigation of bacteria revealed that Actinobacteria, Bacteroidetes, and Proteobacteria in the rhizosphere soil of soybean seedlings were more abundant in the suppressive soil than in the conducive soil. The phylum-level analysis of fungi in rhizosphere soil indicated that relative abundance of Ascomycota was higher in suppressive soil than in the conducive soil, where Basidiomycota was more abundant. Transferring suppressive soil to conducive soil increased the population of Ascomycota in the conducive soil by lowering the populations of Basidiomycota. The genera, such as, Pochonia, Purpureocillium, Fusarium, Stachybotrys that have been well documented as bio-control agents of plant nematodes were far more in the disease suppressive soils. Our results suggested that the plants engage a subset of functional microbial groups in the rhizosphere for initial defense upon nematode attack and protect the plant roots later on by nematodes to response for suppression of SCN in disease-suppressive soils.

Keywords: disease suppressive soil, high-throughput sequencing, rhizosphere microbiome, soybean cyst nematode

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3805 Risk Assessment of Oil Spill Pollution by Integration of Gnome, Aloha and Gis in Bandar Abbas Coast, Iran

Authors: Mehrnaz Farzingohar, Mehran Yasemi, Ahmad Savari

Abstract:

The oil products are imported and exported via Rajaee’s tanker terminal. Within loading and discharging in several cases the oil is released into the berths and made oil spills. The spills are distributed within short time and seriously affected Rajaee port’s environment and even extended areas. The trajectory and fate of oil spills investigated by modeling and parted by three risk levels base on the modeling results. First GNOME (General NOAA Operational Modeling Environment) applied to trajectory the liquid oil. Second, ALOHA (Areal Location Of Hazardous Atmosphere) air quality model, is integrated to predict the oil evaporation path within the air. Base on the identified zones the high risk areas are signed by colored dots which their densities calculated and clarified on a map which displayed the harm places. Wind and water circulation moved the pollution to the East of Rajaee Port that accumulated about 12 km of coastline. Approximately 20 km of north east of Qeshm Island shore is covered by the three levels of risky areas. Since the main wind direction is SSW the pollution pushed to the east and the highest risk zones formed on the crests edges hence the low risk appeared on the concavities. This assessment help the management and emergency systems to monitor the exposure places base on the priority factors and find the best approaches to protect the environment.

Keywords: oil spill, modeling, pollution, risk assessment

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3804 Combined Use of FMRI and Voxel-Based Morphometry in Assessment of Memory Impairment in Alzheimer's Disease Patients

Authors: A. V. Sokolov, S. V. Vorobyev, A. Yu. Efimtcev, V. Yu. Lobzin, I. A. Lupanov, O. A. Cherdakov, V. A. Fokin

Abstract:

Alzheimer’s disease (AD) is the most common form of dementia. Different brain regions are involved to the pathological process of AD. The purpose of this study was to evaluate brain activation by visual memory task in patients with Alzheimer's disease and determine correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. To investigate the organization of memory and localize cortical areas activated by visual memory task we used functional magnetic resonance imaging and to evaluate brain atrophy of patients with Alzheimer's disease we used voxel-based morphometry. FMRI was performed on 1.5 T MR-scanner Siemens Magnetom Symphony with BOLD (Blood Oxygenation Level Dependent) technique, based on distinctions of magnetic properties of hemoglobin. For test stimuli we used series of 12 not related images for "Baseline" and 12 images with 6 presented before for "Active". Stimuli were presented 3 times with reduction of repeated images to 4 and 2. Patients with Alzheimer's disease showed less activation in hippocampal formation (HF) region and parahippocampal gyrus then healthy persons of control group (p<0.05). The study also showed reduced activation in posterior cingulate cortex (p<0.001). Voxel-based morphometry showed significant atrophy of grey matter in Alzheimer’s disease patients, especially of both temporal lobes (fusiform and parahippocampal gyri); frontal lobes (posterior cingulate and superior frontal gyri). The study showed correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. Thus, reduced activation in hippocampal formation and parahippocampal gyri, in posterior cingulate gyrus in patients with Alzheimer's disease correlates to significant atrophy of these regions, detected by voxel-based morphometry, and to deterioration of specific cognitive functions.

Keywords: Alzheimer’s disease, functional MRI, voxel-based morphometry

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3803 Psychological Distress and Quality of Life in Inflammatory Bowel Disease Patients: The Role of Dispositional Mindfulness

Authors: Kelly E. Tow, Peter Caputi, Claudia Rogge, Thomas Lee, Simon R. Knowles

Abstract:

Inflammatory Bowel Disease (IBD) is a serious chronic health condition, characterised by inflammation of the gastrointestinal tract. Individuals with active IBD experience severe abdominal symptoms, which can adversely impact their physical and mental health, as well as their quality of life (QoL). Given that stress may exacerbate IBD symptoms and is frequently highlighted as a contributing factor for the development of psychological difficulties and poorer QoL, it is vital to investigate stress-management strategies aimed at improving the lives of those with IBD. The present study extends on the limited research in IBD cohorts by exploring the role of dispositional mindfulness and its impact on psychological well-being and QoL. The study examined how disease activity and dispositional mindfulness were related to psychological distress and QoL in a cohort of IBD patients. The potential role of dispositional mindfulness as a moderator between stress and anxiety, depression and QoL in these individuals was also examined. Participants included 47 patients with a clinical diagnosis of IBD. Each patient completed a series of psychological questionnaires and was assessed by a gastroenterologist to determine their disease activity levels. Correlation analyses indicated that disease activity was not significantly related to psychological distress or QoL in the sample of IBD patients. However, dispositional mindfulness was inversely related to psychological distress and positively related to QoL. Furthermore, moderation analyses demonstrated a significant interaction between stress and dispositional mindfulness on anxiety. These findings demonstrate that increased levels of dispositional mindfulness may be beneficial for individuals with IBD. Specifically, the results indicate positive links between dispositional mindfulness, general psychological well-being and QoL, and suggest that dispositional mindfulness may attenuate the negative impacts of stress on levels of anxiety in IBD patients. While further research is required to validate and expand on these findings, the current study highlights the importance of addressing psychological factors in IBD and indicates support for the use of mindfulness-based interventions for patients with the disease.

Keywords: anxiety, depression, dispositional mindfulness, inflammatory bowel disease, quality of life, stress

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3802 Management of Gastrointestinal Metastasis of Invasive Lobular Carcinoma

Authors: Sally Shepherd, Richard De Boer, Craig Murphy

Abstract:

Background: Invasive lobular carcinoma (ILC) can metastasize to atypical sites within the peritoneal cavity, gastrointestinal, or genitourinary tract. Management varies depending on the symptom presentation, extent of disease burden, particularly if the primary disease is occult, and patient wishes. Case Series: 6 patients presented with general surgical presentations of ILC, including incomplete large bowel obstruction, cholecystitis, persistent lower abdominal pain, and faecal incontinence. 3 were diagnosed with their primary and metastatic disease in the same presentation, whilst 3 patients developed metastasis from 5 to 8 years post primary diagnosis of ILC. Management included resection of the metastasis (laparoscopic cholecystectomy), excision of the primary (mastectomy and axillary clearance), followed by a combination of aromatase inhibitors, biologic therapy, and chemotherapy. Survival post diagnosis of metastasis ranged from 3 weeks to 7 years. Conclusion: Metastatic ILC must be considered with any gastrointestinal or genitourinary symptoms in patients with a current or past history of ILC. Management may not be straightforward to chemotherapy if the acute pathology is resulting in a surgically resectable disease.

Keywords: breast cancer, gastrointestinal metastasis, invasive lobular carcinoma, metastasis

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3801 SVM-RBN Model with Attentive Feature Culling Method for Early Detection of Fruit Plant Diseases

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

Abstract:

Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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3800 An Optimal Control Model for the Dynamics of Visceral Leishmaniasis

Authors: Ibrahim M. Elmojtaba, Rayan M. Altayeb

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Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years.

Keywords: visceral leishmaniasis, treatment, vaccination, optimal control, numerical simulation

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3799 Diagnosis of Diabetes Using Computer Methods: Soft Computing Methods for Diabetes Detection Using Iris

Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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3798 Finding the Longest Common Subsequence in Normal DNA and Disease Affected Human DNA Using Self Organizing Map

Authors: G. Tamilpavai, C. Vishnuppriya

Abstract:

Bioinformatics is an active research area which combines biological matter as well as computer science research. The longest common subsequence (LCSS) is one of the major challenges in various bioinformatics applications. The computation of the LCSS plays a vital role in biomedicine and also it is an essential task in DNA sequence analysis in genetics. It includes wide range of disease diagnosing steps. The objective of this proposed system is to find the longest common subsequence which presents in a normal and various disease affected human DNA sequence using Self Organizing Map (SOM) and LCSS. The human DNA sequence is collected from National Center for Biotechnology Information (NCBI) database. Initially, the human DNA sequence is separated as k-mer using k-mer separation rule. Mean and median values are calculated from each separated k-mer. These calculated values are fed as input to the Self Organizing Map for the purpose of clustering. Then obtained clusters are given to the Longest Common Sub Sequence (LCSS) algorithm for finding common subsequence which presents in every clusters. It returns nx(n-1)/2 subsequence for each cluster where n is number of k-mer in a specific cluster. Experimental outcomes of this proposed system produce the possible number of longest common subsequence of normal and disease affected DNA data. Thus the proposed system will be a good initiative aid for finding disease causing sequence. Finally, performance analysis is carried out for different DNA sequences. The obtained values show that the retrieval of LCSS is done in a shorter time than the existing system.

Keywords: clustering, k-mers, longest common subsequence, SOM

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3797 Transarterial Chemoembolization (TACE) in Hepatocellular Carcinoma (HCC)

Authors: Ilirian Laçi, Alketa Spahiu

Abstract:

Modality of treatment in hepatocellular carcinoma (HCC) patients depends on the stage of the disease. The Barcelona Clinic Liver Cancer Classification (BCLC) is the preferred staging system. There are many patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. The differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Because of these differences, not all patients benefit equally from TACE. Several tools have been devised to aid the decision-making process, which have shown promising initial results but have failed external evaluation and have not been translated to the clinic aspects. Criteria for treatment decisions in daily clinical practice are needed in all stages of the disease.

Keywords: hepatocellular carcinoma, transarterial chemoembolization, TACE, liver

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3796 Quantitative Evaluation on Community Perceptions of Sanitation and Hygiene in Rural Guatemala

Authors: Akudo Ejelonu, Sarah Willig, J. Anthony Sauder, Heather Murphy, Frances Shofer

Abstract:

Background: The high prevalence of diarrheal diseases in the village of Tzununá, Guatemala is linked to lack of sanitation facilities and handwashing practices. Diarrheal diseases are preventable and improved access to latrines, hygiene education and clean water may improve sanitation by reducing the spread of disease. Objective: Between May 2015-January 2017, the University of Pennsylvania Chapter of Engineers Without Border (PennEWB) and local partners designed an intervention to reduce diarrheal disease by building pour flush latrines in 50 individual households and providing education on the importance of handwashing practice. Design/Methods: Through convenient sampling, we surveyed 45 households to evaluate the community’s knowledge of diarrheal disease, handwashing practices, and maintenance of the latrines. Results: 92% of the study participants experienced decrease of new cases of diarrheal disease after receiving a latrine. Only 11% washed their hands after defecating in the latrine. There was gap in understanding the health outcome of latrine sanitation and handwashing education. The respondents did not connect the reduction of diarrheal disease with latrine use and maintenance. Instead, they associated their motivation for latrine use with aesthetics, proximity to their home, ease and comfort, and reduction of shame. We recommend that PennEWB adopt UNICEF or WHO education on hand washing practice. Conclusion: Social interaction and social pressure drove the household use of latrines. The latrines are being valued and cleaned. The education that the residents received did not target norms and behaviors. Latrines could be used to create a new social norm that supports behavioral change.

Keywords: diarrheal disease, latrine, open defecation, water, sanitation and hygiene

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3795 Frequency of Alloimmunization in Sickle Cell Disease Patients in Africa: A Systematic Review with Meta-analysis

Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

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3794 Cochliobolus sativus: An Important Pathogen of Cereal Crops

Authors: Awet Araya

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Cochliobolus sativus ((anamorphic stage: Bipolaris sorokiniana (synonyms: Helminthosporium sorokinianum, Drechslera sorokiniana, and Helminthosporium sativum)) is an important pathogen of cereal crops. Many other grass species are also hosts for this fungus. Yield losses have been reported from many regions, especially where barley and wheat are commercially cultivated. The fungus has a worldwide distribution. The pathogen causes root rot, seedling blight, spot blotch, head blight, and black point. Environmental conditions affect disease development. Most of the time, fungus survives as mycelia and conidia. Pseudothecium of the fungus is not commonly encountered and probably not important in the epidemiology of the disease. The fungus can be in seed, soil, or in plant parts. Crop rotation, proper fertilization, reducing other stress factors, fungicide treatments, and resistant cultivars may be used for the control of the disease.

Keywords: Cochliobolus sativus, barley, cultivars, root rot

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3793 Gastrointestinal Disturbances in Postural Orthostatic Tachycardia Syndrome (POTS)

Authors: Chandralekha Ashangari, Amer Suleman

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Background and Purpose: The Postural Orthostatic Tachycardia Syndrome (POTS) affects primarily young women. POTS is a form of dysautonomia that is estimated to impact between 1,000,000 and 3,000,000 Americans, and millions more around the world. POTS is a form of orthostatic intolerance that is associated with many Gastrointestinal disturbances. The aim of this study is to determine the Gastrointestinal disturbances in Postural Orthostatic Tachycardia Syndrome (POTS) patients.2. Methods: 249 patients referred to our clinic from January to November with POTS. Reviewed the medical records of 249 POTS patients and gastrointestinal symptoms. Results: however out of 249 patients, 226 patients are female (90.76%; average age 32.69), 23 patients are male (9.24%; average age 27.91) Data analysis: Out of 249 patients 189 patients (76%) had vomiting or nausea, 150 patients (60%) had irritable bowel syndrome, 128 patients (51%) had bloating, 125 patients (50%) had constipation , 80 patients (32%) had abdominal pain, 56 patients (22%) had delayed gastric emptying, 24 patients (10%) had lactose intolerance, 8 patients (3%) had Gastroesophageal reflux disease, 5 patients (2%) had Iron deficiency anemia, 6 patients (2%) had Peptic ulcer disease, 4 patients (2%) had Celiac Disease. Conclusion: Patients with POTS have a very high prevalence of gastrointestinal symptoms however the majority of abnormalities appear to be motility related. Motility testing should be performed be performed in POTS patients. The diagnostic yield of endoscopic procedures appears to be low.

Keywords: gastrointestinal disturbances, Postural Orthostatic Tachycardia Syndrome (POTS), celiac disease, POTS patients

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3792 Health Trajectory Clustering Using Deep Belief Networks

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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3791 The Connection between Social Support, Caregiver Burden, and Life Satisfaction of the Parents Whose Children Have Congenital Heart Disease

Authors: A. Uludağ, F. G. Tufekci, N. Ceviz

Abstract:

Aim: The research has been carried out in order to evaluate caregiver burden, life satisfaction and received social support level of the parents whose children have congenital heart disease; to examine the relationship between the social supports received by them and caregiver burden and life satisfaction. Material and Method: The research which is descriptive and which is searching a relationship has been carried out between the dates June 7, 2012- June 30, 2014, in Erzurum Ataturk University Research and Application Hospital, Department of Pediatrics and Children Cardiology Polyclinic. In the research, it was collaborated with the parents (N = 157) who accepted to participate in, of children who were between the ages of 3 months- 12 years. While gathering the data, a questionnaire, Zarit Caregiver Burden, Life Satisfaction and Social Support Scales have been used. The statistics of the data acquired has been produced by using percentage distribution, mean, and variance and correlation analysis. Ethical principles are followed in the research. Results: In the research, caregiver burden, life satisfaction and social support level received from family (p < 0.05), have been determined higher in the parents whose children have serious congenital heart disease than that of parents whose children have slight disease and social support received from friends has been found lower. It has been determined that there is a strong relation (p < 0.001) through negative direction between both social support levels and caregiver burden of parents; and that there is a strong relation (p < 0.001) through positive direction between both support levels and life satisfaction. Conclusion: That Social Support is in a strong relation with Caregiver Burden through a negative direction and a strong relation with Life Satisfaction through positive direction in parents of all the children who have congenital heart disease requires social support systems to be reinforced. Parents can be led or guided so as to prompt social support systems more.

Keywords: congenital heart disease, child, parents, caregiver burden, life satisfaction, social support

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3790 Joint Modeling of Longitudinal and Time-To-Event Data with Latent Variable

Authors: Xinyuan Y. Song, Kai Kang

Abstract:

Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

Procedia PDF Downloads 113
3789 Children Beliefs about Illness, Treatments and Vaccines after the Experience of Covid 19 Pandemic

Authors: Margarida Maria Cabugueira Csutódio dos Santos, Joana Filipa Pintéus Pereira

Abstract:

The way children understand the concept of health and illness influences their reaction in contexts where these concepts are present (e.g.,illness; vaccination). The recognition of the importance of children's beliefs/representations about health and disease has led to the development of models that seek to explain the development process of these concepts. In the construction of their representations, children are influenced not only by their cognitive competence but also by their life experiences. In the last 3 years, children have experienced a pandemic health crisis that has exposed them to anomalous and stressful situations. Objective: the aim of this study was (1) to identify children’s representations about disease (including symptoms, causes, control/treatment) and prevention (including health procedures and vaccines) and (2) whether COVID19 is mentioned and influences their representations. Methodology: a qualitative study in which 67 children with 7 to 10 years old (mean 8,8) participated. A semi-structured interview was used following the Bibace and Walsh model, focusing on the representation of the disease and its prevention. Results show a marked influence of the lived experience with regard to causes of the disease, disease control and treatment, and adherence to vaccination. Age-dependent differences were found with older children being able to talk about illness and contamination process and younger displaying more basic, concrete and rigid representations. Conclusions: The results of this study bring clues to the adequacy of communication with the child in the context of health and illness and discriminately in a future health pandemic crisis.

Keywords: childen, health beliefs, pediatrics, covid19, vaccines

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3788 A Real-World Evidence Analysis of Associations between Costs, Quality of Life and Disease-Severity Indicators of Alzheimer’s Disease in Thailand

Authors: Khachen Kongpakwattana, Charungthai Dejthevaporn, Orapitchaya Krairit, Piyameth Dilokthornsakul, Devi Mohan, Nathorn Chaiyakunapruk

Abstract:

Background: Although an increase in the burden of Alzheimer’s disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HR-QoL) associated with AD in Low- and Middle-Income Countries (LMICs) is still lacking. We, therefore, aimed to collect real-world cost and HR-QoL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand. Methods: We recruited AD patients aged ≥ 60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HR-QoL and caregiving information using standardized tools. The hospital’s database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HR-QoL. Results: Among 148 community-dwelling patients, average annual total societal costs of AD care were 8,014 US$ [95% Confidence Interval (95% CI): 7,295 US$ - 8,844 US$] per patient. Total costs of patients with severe stage (9,860 US$; 95% CI: 8,785 US$ - 11,328 US$) were almost twice as high as those of mild stage (5,524 US$; 95% CI: 4,649 US$ - 6,593 US$). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient’s HR-QoL (p-value < 0.001). Conclusions: Our real-world findings suggest the distinct major cost driver which results from expensive AD treatment, emphasizing the demand for country-specific cost evidence. Increases in cognitive and functional status are significantly associated with decreases in total costs of AD care and improvement on patient’s HR-QoL.

Keywords: Alzheimer's disease, associations, costs, disease-severity indicators, health-related quality of life

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3787 An Automated System for the Detection of Citrus Greening Disease Based on Visual Descriptors

Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

Abstract:

Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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3786 Heat Transfer and Trajectory Models for a Cloud of Spray over a Marine Vessel

Authors: S. R. Dehghani, G. F. Naterer, Y. S. Muzychka

Abstract:

Wave-impact sea spray creates many droplets which form a spray cloud traveling over marine objects same as marine vessels and offshore structures. In cold climates such as Arctic reigns, sea spray icing, which is ice accretion on cold substrates, is strongly dependent on the wave-impact sea spray. The rate of cooling of droplets affects the process of icing that can yield to dry or wet ice accretion. Trajectories of droplets determine the potential places for ice accretion. Combining two models of trajectories and heat transfer for droplets can predict the risk of ice accretion reasonably. The majority of the cooling of droplets is because of droplet evaporations. In this study, a combined model using trajectory and heat transfer evaluate the situation of a cloud of spray from the generation to impingement. The model uses some known geometry and initial information from the previous case studies. The 3D model is solved numerically using a standard numerical scheme. Droplets are generated in various size ranges from 7 mm to 0.07 mm which is a suggested range for sea spray icing. The initial temperature of droplets is considered to be the sea water temperature. Wind velocities are assumed same as that of the field observations. Evaluations are conducted using some important heading angles and wind velocities. The characteristic of size-velocity dependence is used to establish a relation between initial sizes and velocities of droplets. Time intervals are chosen properly to maintain a stable and fast numerical solution. A statistical process is conducted to evaluate the probability of expected occurrences. The medium size droplets can reach the highest heights. Very small and very large droplets are limited to lower heights. Results show that higher initial velocities create the most expanded cloud of spray. Wind velocities affect the extent of the spray cloud. The rate of droplet cooling at the start of spray formation is higher than the rest of the process. This is because of higher relative velocities and also higher temperature differences. The amount of water delivery and overall temperature for some sample surfaces over a marine vessel are calculated. Comparing results and some field observations show that the model works accurately. This model is suggested as a primary model for ice accretion on marine vessels.

Keywords: evaporation, sea spray, marine icing, numerical solution, trajectory

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3785 2-Dimensional Kinematic Analysis on Sprint Start with Sprinting Performance of Novice Athletes

Authors: Satpal Yadav, Biswajit Basumatary, Arvind S. Sajwan, Ranjan Chakravarty

Abstract:

The purpose of the study was to assess the effect of 2D kinematical selected variables on sprint start with sprinting performance of novice athletes. Six (3 National and 3 State level) athletes of sports authority of India, Guwahati has been selected for this study. The mean (M) and standard deviation (SD) of sprinters were age (17.44, 1.55), height (1.74m, .84m), weight (62.25 kg, 4.55), arm length (65.00 cm, 3.72) and leg length (96.35 cm, 2.71). Biokin-2D motion analysis system V4.5 can be used for acquiring two-dimensional kinematical data/variables on sprint start with Sprinting Performance. For the purpose of kinematic analysis a standard motion driven camera which frequency of the camera was 60 frame/ second i.e. handy camera of Sony Company were used. The sequence of photographic was taken under controlled condition. The distance of the camera from the athletes was 12 mts away and was fixed at 1.2-meter height. The result was found that National and State level athletes significant difference in there, trajectory knee, trajectory ankle, displacement knee, displacement ankle, linear velocity knee, linear velocity ankle, and linear acceleration ankle whereas insignificant difference was found between National and State level athletes in their linear acceleration knee joint on sprint start with sprinting performance. For all the Statistical test the level of significance was set at p<0.05.

Keywords: 2D kinematic analysis, sprinting performance, novice athletes, sprint start

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3784 Human Immunodeficiency Virus Infection/AIDS Abandoned Children in Kenya

Authors: Ruth Muturi Wanjiku

Abstract:

HIV/AIDS in Kenya for unborn and young kids. HIV/AIDS is a significant health concern in Kenya, with an estimated 1.5 million people living with the disease. Unfortunately, many of these individuals are unaware of their HIV status, and the disease continues to spread among the population or unborn kids. HIV/AIDS can be transmitted from an infected mother during pregnancy, childbirth, or breastfeeding. However, with early testing and treatment, the risk of mother-to-child transmission can be significantly reduced. Therefore, it is crucial for pregnant women to get tested and receive appropriate medical care. For young kids, HIV/AIDS education is critical to preventing the spread of the disease. It is essential to teach children about the importance of safe sex practices, avoiding risky behaviors such as sharing needles and getting tested regularly. Additionally, children should be taught about the stigma surrounding HIV/AIDS and encouraged to treat individuals living with the disease with compassion and respect. In conclusion, HIV/AIDS is a significant health concern in Kenya that affects individuals of all ages. For unborn kids, early testing and treatment are critical to reducing the risk of mother-to-child transmission. For young kids, education about HIV/AIDS and safe sex practices is essential to preventing the spread of the disease and reducing stigma. It is essential to promote awareness and encourage individuals to get tested and seek medical care if they believe they may be infected with HIV/AIDS.

Keywords: AIDS, HIV, children, pregnant

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3783 Environmental Parameters Influence on Chronic Obstructive Pulmonary Disease (COPD) Patients’ Quality of Life

Authors: Kwok W. Mui, Ling T. Wong, Nai K. K. Fong

Abstract:

Chronic obstructive pulmonary disease (COPD) is the fifth leading cause of death in Hong Kong. Investigators are eager to explore the environmental risk factors for COPD such as air pollution and occupational exposure. Through a cross-sectional survey, this study investigates the impact of air quality to the quality of life of patients with the COPD in terms of the scores of the (Chinese) chronic respiratory questionnaire (CCRQ) and the measurements of indoor air quality (IAQ) and Moser’s activities of daily living (ADL). Strong relationships between a number of indoor/outdoor environmental parameters were found and CRQ sub-scores for patients of COPD and thus indoor air pollutants must be monitored for future studies related to QOL for patients with COPD.

Keywords: chronic obstructive pulmonary disease (COPD), indoor air pollutants, quality of life, chronic respiratory questionnaire (CRQ)

Procedia PDF Downloads 397