Search results for: disease modeling

Authors: Tadeusz Nowicki, Radosław Pytlak, Robert Waszkowski, Jerzy Bertrandt, Anna Kłos

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This paper presents methods for formal modeling of activities in the area of sanitary inspectors outbreak of food-borne diseases. The models allow you to measure the characteristics of the activities of sanitary inspection and as a result allow improving the performance of sanitary services and thus food security.

Keywords: food-borne disease, epidemic, sanitary inspection, mathematical models

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Authors: Keng H. Kong, Louis C. Tan, Wing L. Aw, Kay Y. Tay

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Background: Fatigue is a common problem in patients with Parkinson's disease, with reported prevalence of up to 70%. Fatigue can be disabling and has adverse effects on patients' quality of life. There is currently no satisfactory treatment of fatigue. Acupuncture is effective in the treatment of fatigue, especially that related to cancer. Its role in Parkinson's disease-related fatigue is uncertain. Aims: To evaluate the clinical efficacy of acupuncture treatment in Parkinson's disease-related fatigue. Hypothesis: We hypothesize that acupuncture is effective in alleviating Parkinson's disease-related fatigue. Design: A single center, randomized, controlled study with two parallel arms. Participants: Forty participants with idiopathic Parkinson's disease will be enrolled. Interventions: Participants will be randomized to receive verum (real) acupuncture or placebo acupuncture. The retractable non-invasive sham needle will be used in the placebo group. The intervention will be administered twice a week for five weeks. Main outcome measures: The primary outcome will be the change in general fatigue score of the multidimensional fatigue inventory at week 5. Secondary outcome measures include other subscales of the multidimensional fatigue inventory, movement disorders society-unified Parkinson's disease rating scale, Parkinson's disease questionnaire-39 and geriatric depression scale. All outcome measures will be assessed at baseline (week 0), completion of intervention (week 5) and 4 weeks after completion of intervention (week 9). Results: To date, 23 participants have been recruited and nine have completed the study. The mean age is 63.5±14.2 years, mean duration of Parkinson’s disease is 6.4±1.8 years and mean MDS-UPDRS score is 8.3±2.8. The mean general fatigue score of the multidimensional fatigue inventory is 13.5±4.6. No significant adverse event related to acupuncture is noted. Potential significance: If the results are as expected, this study will provide preliminary scientific evidence for the efficacy of acupuncture in Parkinson's Disease-related fatigue, and opens the door for a larger multicentre trial to be performed. In the longer term, it may lead to the integration of acupuncture in the care of patients with Parkinson's disease.

Keywords: acupuncture, fatigue, Parkinson's disease, trial

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Authors: Meriche Hacene

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Introduction: Celiac disease (CD) is a chronic immune-mediated enteropathy triggered by gluten found in wheat or oats or rye. Celiac disease is associated with the HLA-DQ2 and HLA-DQ8 susceptibility alleles. This association with the HLA DQ2/DQ8 molecules confirmed the responsibility of genetic factors that intervene in the triggering of the autoimmune process of this condition. Objective: To evaluate the results of HLA DQ2 and HLA DQ8 typing of 40 patients suspected of having CD by PCR-SSP (Polymerase Chain Reaction Sequence Specific Primers). Material and method : 40 patients suspected of celiac disease with IgA transglutaminase serology (-) and duodenal biopsy (+). HLADR/DQ PCR-SSP (fluogen-innotrain) typing was carried out. Results : The average age of adults was 40 years, children: 4 years, the sex ratio was 1M/3F. In our patients the HLA DQ2 allele is found with a frequency of 75%, the DQ8 with a frequency of 25%, 17.5% were HLA-DQ2 homozygous and 15% were HLADQ2/HLADQ8. In our series, HLADQ2, DQ8 are found in almost all patients with a frequency of 95%. 30% of patients in our study had associated positivity of HLA-DRB3, DRB4 or DRB5 alleles. Conclusion : A high prevalence of positivity of HLADQ2 alleles at the expense of HLA DQ8 was found, which is consistent with literature data. These molecules constitute an additional marker for screening and diagnosis of CD.

Keywords: HLA typing, coeliac disease, HLA DQ 2, HLA DQ8

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: Karolina Siejka, Monika Piekarska, Monika Zbroja, Weronika Cyranka, Maryla Kuczynska, Magdalena Grzegorczyk, Malgorzata Nowakowska, Agnieszka Brodzisz, Magdalena Maria Wozniak

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Crohn’s disease is one of chronic inflammatory bowel diseases. It is increasing in prevalence worldwide, especially with young people. The disease usually occurs in the second to the fourth decade of life. Traditionally is diagnosed by clinical indicates, endoscopic, and histological findings. Magnetic Resonance Enterography (MRE) can demonstrate mural and extramural inflammatory signs and complications, which make it a valuable diagnostic modality. The study included 76 adults and 36 children diagnosed with Crohn’s disease. Each patient underwent MRE with intravenous administration of a contrast agent. All the studies were performed using Siemens Aera 1.5T scanner according to a local study protocol. Whenever applicable, MR Enterography findings were verified with endoscopy. Forty adults and all 36 children had an active phase of Crohn’s disease; five adults had a chronic phase of the disease; one adult had both chronic and active inflammatory features. Thirty adults have no sings of pathology. In both adult and pediatric groups the most commonly observed manifestation of active disease was thickened edematous ileum wall (26 adults and 36 children). Adults had Bauhin’s valve edema in 58% cases (n=23) and mesenteric changes in 34% cases (n=9). To compare, 32 children had Bauhin’s valve edema (89%) and, in 23 cases, was found inflammatory infiltration of the peri-intestinal fat (64%). The involvement of the large intestine was more common among children (100%). Complications of Crohn’s disease were found commonly in adults (40% of adults, 22% of children). There were observed 18 fistulas (14 adults, four children) and six abscesses (2 adults, four children). MRE is a reliable method in the evaluation of Crohn’s disease activity, especially of its complications. The lack of radiations makes MRE well-tolerated modality, which can be often repeated, particularly in young patients. The disease had different medical sings depending on age – children often had a more active inflammatory process, but there were more complications in the adult group.

Keywords: Crohn's disease, diagnostics, inflammatory bowel disease, magnetic resonance enterography, MRE

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Ridha Salhi, Mondher Labidi, Fethi Choubani

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Metamaterials have attracted much attention in recent years because of their electromagnetic exquisite proprieties. We will present, in this paper, the modeling of three metamaterial structures by equivalent circuit model. We begin by modeling the SRR (Split Ring Resonator), then we model the HIS (High Impedance Surfaces), and finally, we present the model of the CPW (Coplanar Wave Guide). In order to validate models, we compare the results obtained by an equivalent circuit models with numerical simulation.

Keywords: metamaterials, SRR, HIS, CPW, IDC

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Authors: Svitlana Antonenko, Gennady Telegeev

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Introductive statement: The development of chronic myeloid leukemia (CML) is caused by Bcr-Abl oncoprotein. Modern treatments with tyrosine kinase inhibitors are greatly complicated by the mutational variability of the Bcr-Abl oncoprotein, which causes drug resistance. Therefore, there is an urgent need to develop new approaches to the treatment of the disease, which will allow modeling the level of Bcr-Abl oncoprotein in the cell. Promising in this direction is the identification of proteases that can selectively promote cellular proteolysis of oncoproteins. The aim of the study was to study the effect of the interaction of Bcr-Abl with deubiquitinase USP1 on the level of oncoprotein in CML cells. Methodology: K562 cells were selected for the experiment. Сells were incubated with ML323 inhibitor for 24 hours. Precipitation of endogenous proteins from K562 cell lysate was performed using anti-Bcr-Abl antibodies. Cell lysates and precipitation results were studied by Western blot. Subcellular localization of proteins was studied by immunofluorescence analysis followed by confocal microscopy. The results were analyzed quantitatively and statistically. Major findings: The Bcr-Abl/USP1 protein complex was detected in CML cells, and it was found that inhibition of USP1 deubiquitinating activity by the compound ML323 leads to disruption of this protein complex and a decrease in the level of Bcr-Abl oncoprotein in cells. The interaction of Bcr-Abl with USP1 may result in deubiquitination of the oncoprotein, which disrupts its proteasomal degradation and leads to the accumulation of CML in cells. Conclusion: We believe that the interaction of oncoprotein with USP1 may be one of the prerequisites that contribute to malignant cell transformation due to the deubiquitination of oncoprotein, which leads to its accumulation and disease progression. A correlation was found between the deubiquitinating activity of USP1 and the level of oncoprotein in CML cells. Thus, we identify deubiquitinase USP1 as a promising therapeutic target for the development of a new strategy for the treatment of CML by modulating the level of Bcr-Abl in the cell.

Keywords: chronic myeloid leukemia, Bcr-Abl, USP1, deubiquitination Bcr-Abl, K562 cell

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Manal Al Bahri, Saif Al Mubahisi, Shamsa Al Shahaimi, Asma Al Qasabi, Jamal Al Aghbari

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Introduction: ILD is a common disease worldwide and in Oman. No previous Omani study was published regarding ILD prognosis based on baseline PFT results and other factors. This study aims to determine the severity of ILD by the baseline PFT, correlate between baseline PFT and outcome, and study other factors that influence disease mortality. Method: It is a retrospective cohort study; data was collected from January 2011 to December 2021 from electronic patient records (EPR). Means, Standard Deviations, frequencies, and Chi-square tests were used to examine the different variables in the study. Results: The total population of the study was 146 patients; 87 (59.6%) were females, and 59 (40.4%) were males. The median age was 59 years. Age at diagnosis, CVA, rheumatological disease, and baseline FVC were found to be statistically significant predictors of mortality .59.6% of the patients are diagnosed with IPF. Most of our study patients had mild disease based on baseline FVC. Death was higher with the more severe disease based on FVC. In mild disease (FVC >70%), 26.9% of the patients died. In moderate disease (FVC 50-69%),55.7% of the patients died, and in the severe group (FVC <50 %), 55.1% died. This was statistically significant with a P value of 0. 001. There is no statistically significant difference in the overall survival distribution between the different groups of DLCO. Conclusion: In our study, we found that ILD is more common among females, but death is more common among males. Based on baseline PFT, we can predict mortality by FVC level, as moderate to severe limitation is associated with a lower survival rate. DLCO was not a statistically significant parameter associated with mortality.

Keywords: PFT, ILD, FVC, DLCO, mortality

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Authors: Rasha M. Hussein, Reem M. Hashem, Laila A. Rashed

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Alzheimer’s disease is the most common dementia disease in the elderly. It is characterized by the accumulation of extracellular amyloid β (Aβ) peptides and intracellular hyper-phosphorylated tau protein. In addition, recent evidence indicates that accumulation of intracellular amyloid β peptides may play a role in Alzheimer’s disease pathogenesis. This suggests that intracellular Heat Shock Proteins (HSP) that maintain the protein quality control in the cell might be potential candidates for disease amelioration. DNAJB6, a member of DNAJ family of HSP, effectively prevented the aggregation of poly glutamines stretches associated with Huntington’s disease both in vitro and in cells. In addition, DNAJB6 was found recently to delay the aggregation of Aβ42 peptides in vitro. In the present study, we investigated the ability of DNAJB6 to prevent the aggregation of both intracellular and extracellular Aβ peptides using transfection of HEK293 cells with Aβ-GFP and recombinant Aβ42 peptides respectively. We performed western blotting and immunofluorescence techniques. We found that DNAJB6 can prevent Aβ-GFP aggregation, but not the seeded aggregation initiated by extracellular Aβ peptides. Moreover, DNAJB6 required interaction with HSP70 to prevent the aggregation of Aβ-GFP protein and its J-domain was essential for this anti-aggregation activity. Interestingly, overexpression of other DNAJ proteins as well as HSPB1 suppressed Aβ-GFP aggregation efficiently. Our findings suggest that DNAJB6 is a promising candidate for the inhibition of Aβ-GFP mediated aggregation through a canonical HSP70 dependent mechanism.

Keywords: Aβ, Alzheimer’s disease, chaperone, DNAJB6, aggregation

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Sanskar, Abhinav Pal, Aryush Gupta, Sushil Kumar Mishra

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One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper.

Keywords: plant diseases, machine learning, image processing, deep learning

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: I. Nyoman Mahayasa Adiputra

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Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.

Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city

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Authors: Seung Min Kim, Lyu Jin Jun, Joon Bum Jeong

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The Myxosporea to cause emaciation disease in the olive flounder (Paralichthys olivaceus) is a pathogen to cause severe losses in the aquafarming industry in Korea. The 3,362 bp of DNA nucleotide sequences of four myxosporean strains (EM-HM-12, EM-MA-13, EM-JJ-14, and EM-MS-15) detected by PCR method from olive flounder suffering from emaciation disease in Korea during 2012-2015 were sequenced and deposited in GenBank database (GenBank accession numbers: KU377574, KT321705, KU377575 and KU377573, respectively). The homologies of DNA nucleotide sequences of four strains were compared to each other and were more than 99.7% homologous between the four strains. All of the strains were identified as Parvicapsula petunia based on the results of phylogenetic analysis. The results in this study would be useful for the research of emaciation disease in olive flounder of Korea.

Keywords: disease, emaciation, olive flounder, phylogenetic analysis

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Authors: T. A. Ajiboye

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This study examines the effects of health education programme on knowledge and prevention of cerebrovascular disease among hypertensive patients in University College Hospital, Ibadan. A quasi-experimental design was adopted for the study. 100 hypertensive patients were conveniently selected from general outpatient department in UCH. Data generated were analyzed using ANOVA at 0.05 alpha levels. The findings of the study revealed that health education programme significantly influenced both the knowledge of hypertensive patients (F=22.70; DF=1/99; p < .05) and their attitude (F=10.377; DF=1/99; p < .05) on cerebrovascular disease. Findings also discovered that health education programme significantly reduce the complication of hypertension to cerebrovascular disease (F= 16.41; DF=7/286; p < 0.05) among the hypertensive patients at UCH. Based on the findings, it is recommended that hypertensive patients should relieve themselves from stress, engage themselves on regular exercises, compliance with drug and diet regimes coupled with keeping up of regular appointment. Government should design health information that will center on hypertension and cerebrovascular disease so as to keep health and community development problems to the barest minimum. Finally, there should be provision of social amenities and recreational centers, as this will prevents hypertension problems.

Keywords: cerebrovascular disease, effectiveness, health education, hypertension, knowledge, prevention

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Authors: Ozge Yilmaz Kusbeci, Ipek Inci

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Aim: Musculoskeletal problems are very common in Parkinson’s disease (PD). They affect quality of life and cause disabilities. However they are under-evaluated, and under-treated. The aim of this study is to evaluate the prevalence and clinical features of musculoskeletal problems in patients with Parkinson disease (PD) compared to controls. Methods: 50 PD patients and 50 age and sex matched controls were interviewed by physicians about their musculoskeletal problems. Results: The prevalence of musculoskeletal problems was significantly higher in the PD group than in the control group (p < 0.05). Commonly involved body sites were the shoulder, low back, and knee. The shoulder and low back was more frequently involved in the PD group than in the control group. However, the knee was similarly involved in both groups. Among the past diagnoses associated with musculoskeletal problems, frozen shoulder, low back pain and osteoporosis more common in the PD group than in the control group (p < 0.05). Furthermore, musculoskeletal problems in the PD group tended to receive less treatment than that of the control group. Conclusion: Musculoskeletal problems were more common in the PD group than in the controls. Therefore assessment and treatment of musculoskeletal problems could improve quality of life in PD patients.

Keywords: parkinson disease, musculoskeletal problems, quality of life, PD disease

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Authors: Eman Ahmed Alsaleh

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Background: Many studies published in other countries identified certain perceived benefits and barriers to physical activity among patients with coronary heart disease. Nevertheless, there is no data about the issue relating to Jordanian patients with coronary heart disease. Objective: This study aimed to describe the prevalence of level of physical activity, benefits of and barriers to physical activity as perceived by Jordanian patients with coronary heart disease, and the relationship between physical activity and perceived benefits of and barriers to physical activity. In addition, it focused on examining the influence of selected sociodemographic and health characteristics on physical activity and the perceived benefits of and barriers to physical activity. Methods: A cross-sectional design was performed on a sample of 400 patients with coronary heart disease. They were given a list of perceived benefits and barriers to physical activity and asked to what extent they disagreed or agreed with each. Results: Jordanian patients with coronary heart disease perceived various benefits and barriers to physical activity. Most of these benefits were physiologically related (average mean = 5.7, SD = .7). The most substantial barriers to physical activity as perceived by the patients were: feeling anxiety, not having enough time, lack of interest, bad weather, and feeling of being uncomfortable. Sociodemographic and health characteristics that significantly influenced perceived barriers to physical activity were age, gender, health perception, chest pain frequency, education, job, caring responsibilities, ability to travel alone, smoking, and previous and current physical activity behaviour. Conclusion: This research demonstrates that patients with coronary heart disease have perceived physiological benefits of physical activity, and they have perceived motivational, physical health, and environmental barriers to physical activity, which is significant in developing intervention strategies that aim to maximize patients' participation in physical activity and overcome barriers to physical activity.

Keywords: prevalence, coronary heart disease, physical activity, perceived barriers

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

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Authors: Mohammed A. Alfayyadh, Halla A. AlAbdulhadi, Mahdi H. Almubarak

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Purpose: Eales’ disease is an idiopathic vasculitis that affects the peripheral retina. It is characterized by recurrent vitreous hemorrhage as a complication of retinal neovascularization. It is more prevalent in India and affects young males. Here we present a patient with neovascular glaucoma as a rare first presentation of Eales’ disease. Observations: This is a 24-year-old Indian gentleman, who complained of a sudden decrease in vision in the left eye over less than 24 hours, along with frontal headache and eye pain for the last three weeks. Ocular examination revealed peripheral retinal ischemia in the right eye, very high intraocular pressure, rubeosis iridis, vitreous hemorrhage and extensive retinal ischemia in the left eye, vascular sheathing and neovascularization in both eyes. Purified protein derivative skin test was positive. The patient was managed with anti-glaucoma, intravitreal anti-vascular endothelial growth factor and laser photocoagulation. Systemic steroids and anti-tuberculous therapy were also initiated. Conclusions: Neovascular glaucoma is an infrequent complication of Eales’ disease. However, the lack of early detection of the disease in the early stages might lead to such serious complication.

Keywords: case report, Eales’ disease, mycobacterium tuberculosis, neovascular glaucoma

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Authors: Sumit Kumar, Sunil Kumar, Chandan Deep Singh

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This paper presents modeling and simulation of flexible robot in an underwater environment. The underwater environment completely contrasts with ground or space environment. The robot in an underwater situation is subjected to various dynamic forces like buoyancy forces, hydrostatic and hydrodynamic forces. The underwater robot is modeled as Rayleigh beam. The developed model further allows estimating the deflection of tip in two directions. The complete dynamics of the underwater robot is analyzed, which is the main focus of this investigation. The control of robot trajectory is not discussed in this paper. Simulation is performed using Symbol Shakti software.

Keywords: bond graph modeling, dynamics. modeling, rayleigh beam, underwater robot

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Authors: Sadia Arshad

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The new coronavirus disease or COVID-19 still poses an alarming situation around the world. Modeling based on the derivative of fractional order is relatively important to capture real-world problems and to analyze the realistic situation of the proposed model. Weproposed a mathematical model for the investigation of COVID-19 dynamics in a generalized fractional framework. The new model is formulated in the Caputo sense and employs a nonlinear time-varying transmission rate. The existence and uniqueness solutions of the fractional order derivative have been studied using the fixed-point theory. The associated dynamical behaviors are discussed in terms of equilibrium, stability, and basic reproduction number. For the purpose of numerical implementation, an effcient approximation scheme is also employed to solve the fractional COVID-19 model. Numerical simulations are reported for various fractional orders, and simulation results are compared with a real case of COVID-19 pandemic. According to the comparative results with real data, we find the best value of fractional orderand justify the use of the fractional concept in the mathematical modelling, for the new fractional modelsimulates the reality more accurately than the other classical frameworks.

Keywords: fractional calculus, modeling, stability, numerical solution

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Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

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Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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Authors: Dana Weimann Saks

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This study aimed to examine the use of the internet as a source of health-related information (HRI), as well as the change in attitudes following the online search for HRI. The current study sample included 88 participants, randomly divided into two experimental groups. One was given the name of an unfamiliar disease and told to search for information about it using various search engines, and the second was given a text about the disease from a credible scientific source. The study findings show a large percentage of participants used the internet as a source of HRI. Likewise, no differences were found in the extent to which the internet was used as a source of HRI when demographics were compared. Those who searched for the HRI on the internet had more negative opinions and believed symptoms of the disease were worse than the average opinion among those who obtained the information about the disease from a credible scientific source. The Internet clearly influences the participants’ beliefs, regardless of demographic differences.

Keywords: health-related information, internet, young adults, HRI

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Authors: Shigeyuki Haruyama, Ken Kaminishi, Junji Kaneko, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

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This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physics fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: system model, physical models, empirical models, conservation law, differential algebraic equation, object-oriented

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Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach using the Healthcare Multi-Agent System. The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are: The Behavioral Pattern Analysis (BPA) modeling methodology. The development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases, Healthcare Multi-Agent System

Procedia PDF Downloads 551

Authors: S. P. Chintan, A. M. Khoja, M. Modi, R. K. Chopra, S. Garde, D. Jain, O. Kajale

Abstract:

Pulmonary Hypertension is a rare but debilitating disease that affects individuals of all ages and walks of life. As recent as 15 years ago, a patient diagnosed with PH was given an average survival rate of 2.8 years. Recent advances in treatment options have allowed patients to improve quality o and quantity of life. Initial screening for PH is through echocardiography with final diagnosis confirmed through right heart catheterization. PH is now considered to have five major classifications with subgroups among each. The mild to moderate PH is common in chronic lung diseases like Chronic obstructive pulmonary diseases and Interstitial lung disease. But very severe PH is noted in few cases. In COPD patients, PH is associated with an increased risk of severe exacerbations and a reduced life expectancy. Similarly, in patients with ILD, the presence of PH correlates with a poor prognosis. Early diagnosis is essential to slow disease progression. We report here five cases of severe PH (Out of Proportion) of which four cases were of COPD and another one of IPF (UIP pattern). There echocardiography showed gross RA/RV dilatation, interventricular septum bulging to the left and mPAP of more than 100 mmHg in all the five cases. These patients were put on LTOT, pulmonary rehabilitation, combination pharmacotherapy of vasodilators and diuretics in continuation to the treatment of underlying disease. As these patients have grave prognosis close monitoring and follow up is required. Physicians associated with respiratory care and treating chronic lung disease should have knowledge in the diagnosis and management of patients with PH.

Keywords: COPD, pulmonary hypertension, chronic lung disease, India

Procedia PDF Downloads 357

Authors: Anucha Taiwong, Nirobol Kanogsunthornrat

Abstract:

This predictive research aimed to investigate the symptom clusters that influence the quality of life among patients with chronic kidney disease, as indicated in the Theory of Unpleasant Symptoms. The purposive sample consisted of 150 patients with stage 3-4 chronic kidney disease who received care at an outpatient chronic kidney disease clinic of a tertiary hospital in Roi-Et province. Data were collected from January to March 2016 by using a patient general information form, unpleasant symptom form, and quality of life (SF-36) and were analyzed by using descriptive statistics, factor analysis, and multiple regression analysis. Findings revealed six core symptom clusters including symptom cluster of the mental and emotional conditions, peripheral nerves abnormality, fatigue, gastro-intestinal tract, pain and, waste congestion. Significant predictors for quality of life were the two symptom clusters of pain (Beta = -.220; p < .05) and the mental and emotional conditions (Beta=-.204; p<.05) which had predictive value of 19.10% (R2=.191, p<.05). This study indicated that the symptom cluster of pain and the mental and emotional conditions would worsen the patients’ quality of life. Nurses should be attentive in managing the two symptom clusters to facilitate the quality of life among patients with chronic kidney disease.

Keywords: chronic kidney disease, symptom clusters, predictors of quality of life, pre-dialysis

Procedia PDF Downloads 318

Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Intelligent Agent Reservation System (IARS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are developing the Behavioral Pattern Analysis (BPA) modeling methodology, and developing an interactive software tool (DECISION) which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, intelligent agent, reservation system, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

Procedia PDF Downloads 484