Search results for: Brown rot disease

Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.

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Authors: Ling-Lih Shen, Feng-Chuan Pan

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Chronic diseases prevailed along with economic growth as well as life style changed in recent years in Taiwan. According to the governmental statistics, hypertension related disease is the tenth of death causes with 1,816 died directly from hypertension in 2010. There were more death causes amongst the top ten had been proofed that having strong association with the hypertension, such as heart diseases, cardiovascular diseases, and diabetes. Hypertension or High blood pressure is one of the major indicators for chronic diseases, and was generally perceived as the major causes of mortality. The literature generally suggested that regular physical exercise was helpful to prevent the occurrence or to ease the progress of a hypertension. This paper reported the process and outcomes in detailed of an improvement project of physical exercise intervention specific for hypertension patients. Physical information were measured before and after the project to obtain information such as weight, waistline, cholesterol (HD & LD), blood examination, as well as self-perceived health status. The intervention project involved a six-week exercise program, of which contained three times a week, 30 minutes of tutored physical exercise intervention. The project had achieved several gains in changing the subjects- behavior in terms of many important biophysical indexes. Around 20% of the participants had significantly improved their cholesterols, BMI, and changed unhealthy behaviors. Results from the project were encouraging, and would be good reference for other samples.

Keywords: Intervention, biological information, hypertension patients, behavioral changes, chronic disease

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Authors: Paria Soleimani, Arezoo Neshati

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Myocardial infarction is one of the leading causes of death in the world. Some of these deaths occur even before the patient reaches the hospital. Myocardial infarction occurs as a result of impaired blood supply. Because the most of these deaths are due to coronary artery disease, hence the awareness of the warning signs of a heart attack is essential. Some heart attacks are sudden and intense, but most of them start slowly, with mild pain or discomfort, then early detection and successful treatment of these symptoms is vital to save them. Therefore, importance and usefulness of a system designing to assist physicians in early diagnosis of the acute heart attacks is obvious. The main purpose of this study would be to enable patients to become better informed about their condition and to encourage them to seek professional care at an earlier stage in the appropriate situations. For this purpose, the data were collected on 711 heart patients in Iran hospitals. 28 attributes of clinical factors can be reported by patients; were studied. Three logistic regression models were made on the basis of the 28 features to predict the risk of heart attacks. The best logistic regression model in terms of performance had a C-index of 0.955 and with an accuracy of 94.9%. The variables, severe chest pain, back pain, cold sweats, shortness of breath, nausea and vomiting, were selected as the main features.

Keywords: Coronary heart disease, acute heart attacks, prediction, logistic regression.

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Authors: Benjamin Osei-Tutu

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Food contaminated with biological, chemical and physical hazards usually leads to foodborne illnesses which in turn increase the disease burden of developing and developed economies. Restaurants play a key role in the food service industry and violations in application of standardized food safety management systems in these establishments have been associated with foodborne disease outbreaks. This study was undertaken to assess the level of compliance to the Code of practice that was developed and implemented after conducting needs assessment of the food safety management systems employed by the Food Service Establishments in Ghana. Data on pre-licence inspections were reviewed to assess the compliance of the Food Service Establishments. During the period under review (2012-2016), 74.52% of the food service facilities in the hospitality industry were in compliance with the FDA’s code of practice. Main violations observed during the study bordered on facility layout and fabrication (61.8%) and this is because these facilities may not have been built for use as a food service establishment. Another fact that came to the fore was that the redesigning of the facilities to bring them into compliance required capital intensive investments, which some establishments are not prepared for. Other challenges faced by the industry regarded issues on records and documentations, personnel facilities and hygiene, raw materials acquisition, storage and control, and cold storage.

Keywords: Assessment, Accra, food safety management systems, restaurants, hotel.

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Authors: David J. Russell SC

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Widespread use of asbestos over the last century has left a terrible legacy of lung disease. Doctors knew of the health risks long ago, but almost nothing was done to protect workers and the public. Some aspects of nanotechnology may have risks similar to asbestos.

Keywords: Asbestos, causation, nanotechnology.

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Authors: Grace Sahaya Sheba, P. Omegala Priyakumari, M. Gunasekaran

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L-asparagine admixture Paranitrophenol (LAPNP) single crystals were grown successfully by solution method with slow evaporation technique at room temperature. Crystals of size 12mm×5 mm×3mm have been obtained in 15 days. The grown crystals were Brown color and transparent. The solubility of the grown samples has been found out at various temperatures. The lattice parameters of the grown crystals were determined by X-ray diffraction technique. The reflection planes of the sample were confirmed by the powder X-ray diffraction study and diffraction peaks were indexed. Fourier transform infrared (FTIR) studies were used to confirm the presence of various functional groups in the crystals. UV–visible absorption spectrum was recorded to study the optical transparency of grown crystal. The nonlinear optical (NLO) property of the grown crystal was confirmed by Kurtz–Perry powder technique and a study of its second harmonic generation efficiency in comparison with potassium dihydrogen phosphate (KDP) has been made. The mechanical strength of the crystal was estimated by Vickers hardness test. The grown crystals were subjected to thermo gravimetric and differential thermal analysis (TG/DTA). The dielectric behavior of the sample was also studied

Keywords: Characterization, Microhardnes, Non-linear optical materials, Solution growth, Spectroscopy, XRD.

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Authors: Zuhrotun Ulya, Muchammad Syamsulhadi, Debree Septiawan

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Patients with bipolar disorder are three times more likely to suffer cardiovascular disorders than the general population, which will influence their level of morbidity and rate of mortality. Bipolar disorder also affects the pulmonary system. The choice of long term-monotherapy and other combinative therapies have clinical impacts on patients. This study investigates the case of a woman who has been suffering from bipolar disorder for 16 years, and who has a history of Steven Johnson Syndrome. At present she is suffering also from cardiovascular and pulmonary disorder. An analysis of the results of this study suggests that there is a relationship between cardiovascular disorder, drug therapies, Steven Johnson Syndrome and mood stabilizer obtained from the PubMed, Cochrane, Medline, and ProQuest (publications between 2005 and 2015). Combination therapy with mood stabilizer is recommended for patients who do not have side effect histories from these drugs. The replacement drugs and combinations may be applied, especially for those with bipolar disorders, and the combination between atypical antipsychotic groups and mood stabilizers is often made. Clinicians, however, should be careful with the patients’ physical and metabolic changes, especially those who have experienced long-term therapy and who showed a history of Steven Johnson Syndrome (for which clinicians probably prescribed one type of medicine).

Keywords: Cardio-pulmonary disease, bipolar disorder, Steven Johnson Syndrome, therapy.

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Authors: Ratnakar Tripathi, Rajnikant Mishra

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The PAX6, a transcription factor, is essential for the morphogenesis of the eyes, brain, pituitary and pancreatic islets. In rodents, the loss of Pax6 function leads to central nervous system defects, anophthalmia, and nasal hypoplasia. The haplo-insufficiency of Pax6 causes microphthalmia, aggression and other behavioral abnormalities. It is also required in brain patterning and neuronal plasticity. In human, heterozygous mutation of Pax6 causes loss of iris [aniridia], mental retardation and glucose intolerance. The 3- deletion in Pax6 leads to autism and aniridia. The phenotypes are variable in peneterance and expressivity. However, mechanism of function and interaction of PAX6 with other proteins during development and associated disease are not clear. It is intended to explore interactors of PAX6 to elucidated biology of PAX6 function in the tissues where it is expressed and also in the central regulatory pathway. This report describes In-silico approaches to explore interacting proteins of PAX6. The models show several possible proteins interacting with PAX6 like MITF, SIX3, SOX2, SOX3, IPO13, TRIM, and OGT. Since the Pax6 is a critical transcriptional regulator and master control gene of eye and brain development it might be interacting with other protein involved in morphogenesis [TGIF, TGF, Ras etc]. It is also presumed that matricelluar proteins [SPARC, thrombospondin-1 and osteonectin etc] are likely to interact during transport and processing of PAX6 and are somewhere its cascade. The proteins involved in cell survival and cell proliferation can also not be ignored.

Keywords: Interacting Proteins, Pax6, PIP, STRING

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Authors: Laila Ozola, Evita Straumite

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Celiac disease is a permanent enteropathy caused by the ingestion of gluten, a protein occurring in wheat, rye and barley. The only way of the effective daily treatment is a strict gluten-free diet. From the investigation of products available in the local market, it was found that Latvian producers do not offer gluten-free products. The aim of this research was to study and analyze changes of celiac patient’s attitude to gluten-free product quality and availability in the Latvian market and purchasing habits. The survey was designed using website www.visidati.lv, and a questionnaire was sent to people suffering from celiac disease. The first time the respondents were asked to fill in the questionnaire in 2011, but now repeatedly from the beginning of September 2013 till the end of January 2014. The questionnaire was performed with 75 celiac patients, respondents were from all Latvian regions and they answered 16 questions. One of the most important questions was aimed to find out consumers’ opinion about quality of gluten-free products, consumption patterns of gluten-free products, and, moreover, their interest in products made in Latvia. Respondents were asked to name gluten-free products they mainly buy and give specific purchase locations, evaluate the quality of products and necessity for products produced in Latvia. The results of questionnaire show that the consumers are satisfied with the quality of gluten-free flour, flour blends, sweets and pasta, but are not satisfied with the quality of bread and confectionery available in the Latvian markets.

Keywords: Consumers, gluten-free products, quality, survey.

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Authors: Ammal M. Metwally, Ghada A. Abdel-Latif, Walaa A. Fouad, Thanaa M. Rabah, Amira Mohsen, Fatma A. Shaaban, Iman I. Salama

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The study aimed at determining the impact of chronic hepatitis C virus (HCV) infection on patients’ Quality of Life (QoL), its relation to geographical characteristics of patients, awareness of the disease, treatment regimen, co-morbid psychiatric or other diseases. 457 patients were randomly selected from ten National Treatment Reference Centers of Ministry of Health hospitals from four community locations representing Egypt. Health related QoL assessment questionnaire with the 36-item Short Form used for assessment of the enrolled patients. The study showed no significant difference between HCV patients in different governorates as regards total QoL. Females, illiterate patients and those had bilharziasis, diabetes mellitus, hypertension or were depressed had significantly the lowest QoL score. HCV patients who knew the danger of the disease had significant lower mean score of physical and mental health components. Optimal care of overall well-being of HCV patients requires adequate knowledge of their neurological and psychological status. It is important to know how to cope with having a family member with hepatitis C and more importantly to know what should you say and what shouldn’t you say as a positive hopeful attitude is essential for combating HCV chronic infection.

Keywords: Hepatitis C virus chronic infection, physical health component and mental health component of QoL, total quality of life.

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Authors: Nevena Stolba, A Min Tjoa

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Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.

Keywords: data mining, data warehousing, decision-support systems, evidence-based medicine.

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Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: Fuzzy C-means clustering, Fuzzy C-means clustering based attribute weighting, Pima Indians diabetes dataset, SVM.

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Authors: N. Hadthamard, P. Chaumpluk, M. Buanong, P. Boonyaritthongchai, C. Wongs-Aree

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Ripe ‘Nam Dok Mai’ mango (Mangifera indica L.) is an important exported fruit of Thailand, but rapidly declined in the quality attributes mainly by infection of anthracnose and stem end rot diseases. Multilayer coating is considered as a developed technique to maintain the postharvest quality of mangoes. The utilization of alternated coating by matching oppositely electrostatic charges between 0.1% chitosan and 0.1% polystyrene sulfonate (PSS) was studied. A number of the coating layers (layer by layer) were applied on mature green ‘Nam Dok Mai No.4’ mangoes prior to storage at 25 ^oC, 65-70% relative humidity (RH). There were significant differences in some quality attributes of mangoes coated by 3½ layers, 4½ layers and 5½ layers. In comparison to coated mangoes, uncoated fruits were higher in weight loss, total soluble solids, respiration rate, ethylene production and disease incidence except the titratable acidity. Coating fruit at 3½ layers exhibited the ripening delay and reducing disease infection without off flavour. On the other hand, fruit coated with 5½ layers comprised the lowest acceptable score, caused by exhibiting disorders from fermentation at the end of storage. As a result, multilayer coating between chitosan and PSS could effectively maintain the postharvest quality of mango, but number of coating layers should be thoroughly considered.

Keywords: Multilayer, chitosan, polystyrene sulfonate, Nam Dok Mai No.4.

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Authors: Arshad Javaid, Syeda F. Naqvi

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Macrophomina phaseolina is a devastating soil-borne fungal plant pathogen that causes charcoal rot disease in many economically important crops worldwide. So far, no registered fungicide is available against this plant pathogen. This study was planned to examine the antifungal activity of an allelopathic grass Cenchrus pennisetiformis (Hochst. & Steud.) Wipff. for the management of M. phaseolina isolated from cowpea [Vigna unguiculata (L.) Walp.] plants suffering from charcoal rot disease. Different parts of the plants viz. inflorescence, shoot and root were extracted in methanol. Laboratory bioassays were carried out using different concentrations (0, 0.5, 1.0, …, 3.0 g mL-1) of methanolic extracts of the test allelopathic grass species to assess the antifungal activity against the pathogen. In general, extracts of all parts of the grass exhibited antifungal activity. All the concentrations of methanolic extracts of shoot and root significantly reduced fungal biomass by 20–73% and 40–80%, respectively. Methanolic shoot extract was fractionated using n-hexane, chloroform, ethyl acetate and n-butanol. Different concentrations of these fractions (3.125, 6.25, …, 200 mg mL-1) were analyzed for their antifungal activity. All the concentrations of n-hexane fraction significantly reduced fungal biomass by 15–96% over corresponding control treatments. Higher concentrations (12.5–200 mg mL-1) of chloroform, ethyl acetate and n-butanol also reduced the fungal biomass significantly by 29–100%, 46–100% and 24–100%, respectively.

Keywords: Antifungal activity, Cenchrus pennisetiformis, Macrophomina phaseolina, natural fungicides

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Authors: R. Litt, A. Brown

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Aims: We aimed to assess the efficiency of ‘Attend Anywhere’ orthodontic clinics within a district general hospital during COVID- 19. Our secondary aim was to pilot a questionnaire to assess patient satisfaction with virtual orthodontic appointments. Design: The study design is a service evaluation including pilot questionnaire. Methods: The average number of patients seen per virtual clinic and the number of patients failing to attend was compared to face-to-face clinics. The capability of virtual appointments to be successful in preventing the need for a face-to-face appointment was assessed. Patients were invited to complete a telephone pilot questionnaire focusing on patient satisfaction and accessibility. Results: There was a small increase in the number of patients failing to attend virtual appointments, with a third of the patients who did not attend failing to receive the appointment link. 81.9% of virtual clinic appointments were successful and prevented the need for a face-to-face appointment. Overall patients were very satisfied with their virtual orthodontic appointment and the majority required no assistance to access the service. Conclusions: The use of ‘Attend Anywhere’ clinics in orthodontics offers patients and clinicians an effective and efficient alternative to face-to-face appointments that patients on average find easy to use and completely satisfactory.

Keywords: Clinics, COVID-19, orthodontics, patient satisfaction, virtual.

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Authors: Ime R. Udotong, Justina I. R. Udotong, Ofonime U. M. John

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Ibeno, Nigeria hosts the operational base of Mobil Producing Nigeria Unlimited (MPNU), a subsidiary of ExxonMobil and the current highest oil & condensate producer in Nigeria. Besides MPNU, other oil companies operate onshore, on the continental shelf and deep offshore of the Atlantic Ocean in Ibeno, Nigeria. This study was designed to delineate oil polluted sites in Ibeno, Nigeria using geophysical methods of electrical resistivity (ER) and ground penetrating radar (GPR). Results obtained revealed that there have been hydrocarbon contaminations of this environment by past crude oil spills as observed from high resistivity values and GPR profiles which clearly show the distribution, thickness and lateral extent of hydrocarbon contamination as represented on the radargram reflector tones. Contaminations were of varying degrees, ranging from slight to high, indicating levels of substantial attenuation of crude oil contamination over time. Moreover, the display of relatively lower resistivities of locations outside the impacted areas compared to resistivity values within the impacted areas and the 3-D Cartesian images of oil contaminant plume depicted by red, light brown and magenta for high, low and very low oil impacted areas, respectively confirmed significant recent pollution of the study area with crude oil.

Keywords: Electrical resistivity, geophysical investigations, ground penetrating radar, oil-polluted sites.

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Authors: M. J. Pourvaghar, M. E. Bahram

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Obesity and overweight is one of the most common metabolic disorders in industrialized countries and in developing countries. One consequence of pathological obesity is cardiovascular disease and metabolic syndrome. Chemerin is an adipocyne that plays a role in the regulation of the adipocyte function and the metabolism of glucose in the liver and musculoskeletal system. Most likely, chemerin is involved in obesity-related disorders such as type 2 diabetes and cardiovascular disease. Aerobic exercises reduce the level of chemerin and cause macrophage penetration into fat cells and inflammatory factors. Several efforts have been made to clarify the cellular and molecular mechanisms of hypertrophy and muscular atrophy. Myostatin, a new member of the TGF-β family, is a transforming growth factor β that its expression negatively regulates the growth of the skeletal muscle; and the increase of this hormone has been observed in conditions of muscular atrophy. While in response to muscle overload, its levels decrease after the atrophy period, TGF-β is the most important cytokine in the development of skeletal muscle. Myostatin plays an important role in muscle control, and animal and human studies show a negative role of myostatin in the growth of skeletal muscle. Separation of myostatin from Golgi begins on the ninth day of the onset period and continues until birth at all times of muscle growth. Higher levels of myostatin are found in obese people. Resistance training for 10 weeks could reduce levels of plasma myostatin.

Keywords: Chemerin, myostatin, obesity, physical activity.

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Authors: Simon B. N. Thompson

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Cortisol is important to our immune system, regulates our stress response, and is a factor in maintaining brain temperature. Saliva cortisol is a practical and useful non-invasive measurement that signifies the presence of the important hormone. Electrical activity in the jaw muscles typically rises when the muscles are moved during yawning and the electrical level is found to be correlated with the cortisol level. In two studies using identical paradigms, a total of 108 healthy subjects were exposed to yawning-provoking stimuli so that their cortisol levels and electrical nerve impulses from their jaw muscles was recorded. Electrical activity is highly correlated with cortisol levels in healthy people. The Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details were collected and exclusion criteria applied for voluntary recruitment: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, and stroke. Significant differences were found between the saliva cortisol samples for the yawners as compared with the non-yawners between rest and post-stimuli. Significant evidence supports the Thompson Cortisol Hypothesis that suggests rises in cortisol levels are associated with yawning. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: Cortisol, Diagnosis, Neurological Disease, Thompson Cortisol Hypothesis, Yawning.

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Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structureprocess- property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: Biosensor, design, DNA, molecular dynamics simulation.

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Authors: Anis S. Shuib, Peter R. Hoskins, William J. Easson

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Cardiovascular disease mostly in the form of atherosclerosis is responsible for 30% of all world deaths amounting to 17 million people per year. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis. The initiation and progression of the disease is strongly linked to the hemodynamic environment near the vessel wall. The aim of this study is to validate the flow of blood mimic through an arterial stenosis model with computational fluid dynamics (CFD) package. In experiment, an axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. Particle image velocimetry (PIV) was used to characterize the flow. The fluid consists of rigid spherical particles suspended in waterglycerol- NaCl mixture. The particles with 20 μm diameter were selected to follow the flow of fluid. The flow at Re=155, 270 and 390 were investigated. The experimental result is compared with FLUENT simulated flow that account for viscous laminar flow model. The results suggest that laminar flow model was sufficient to predict flow velocity at the inlet but the velocity at stenosis throat at Re =390 was overestimated. Hence, a transition to turbulent regime might have been developed at throat region as the flow rate increases.

Keywords: Atherosclerosis, Particle-laden flow, Particle imagevelocimetry, Stenosis artery

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: Metagenomics, phenotype prediction, deep learning, embeddings, multiple instance learning.

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI.

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Authors: Evy Latifah, Eko Widaryanto, M. Dawam Maghfoer, Arifin

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Tomato (Lycopersicon esculentum Mill.) is potential vegetables to develop, because it has high economic value and has the potential to be exported. There is a decrease in tomato productivity due to unfavorable growth conditions such as bacterial wilt, fusarium wilt, high humidity, high temperature and inappropriate production technology. Grafting technology is one alternative technology. In addition to being able to control the disease in the soil, grafting is also able to increase the growth and yield of production. Besides, it is also necessary to know the economic benefits if using grafting technology. A promising eggplant rootstock for tomato grafting is Solanum torvum. S. torvum is selected as a rootstock with high compatibility. The purpose of this research is to know the effect of grafting several varieties of tomatoes with Solanum torvum as a rootstock. The experiment was conducted in Agricultural Extension Center Pare. Experimental Garden of Pare Kediri sub-district from July to early December 2016. The materials used were tomato Cervo varieties, Karina, Timoty, and Solanum torvum. Economic analysis, growth, and yield including plant height, number of leaves, percentage of disease and tomato production were used as performance measures. The study showed that grafting tomato Timoty scion with Solanum torvum as rootstock had higher production. Financially, grafting tomato Timoty and Cervo scion had higher profit about. 28,6% and 16,3% compared to Timoty and Cervo variety treatment without grafting.

Keywords: Grafting technology, economic analysis, growth, yield of tomato, Solanum torvum.

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Authors: S. Firouzi, M.R. Alizadeh, S. Minaei

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A study was carried out at the Rice Research Institute of Iran (RRII) to investigate the effect of rollers differential peripheral speed of commercial rubber roll husker and paddy moisture content on the husking index and percentage of broken rice. The experiment was conducted at six levels of rollers differential speed (1.5, 2.2, 2.9, 3.6, 4.3 and 5 m/s) and three levels of paddy moisture content (8-9, 10-11 and 12-13% w.b.). Two common paddy varieties namely, Binam and Khazer, were selected for this study. Results revealed that the effect of rollers differential speed and moisture content significantly (P<0.01) affected percentage of broken brown rice and paddy husking index. Average broken kernel percentage increased from 13 to 14.61% while husking index decreased from 71.64 to 61.81%, as paddy moisture content increased from 8-9 to 12-13%. It was observed that amount of broken rice decreased from 18.83 to 9.97%, when rollers differential speed varied from 1.5 to 5 m/s, while the husking index initially increased and then started to decrease. The mean value of husking index for Khazar variety (64.71%) was significantly lower than that for Binam variety (69.2%). It was concluded that rollers differential speed of 2.9 m/s and moisture content of 8-9% was the most appropriate combination for paddy husking of Binam and Khazar varieties in rubber roll husker.

Keywords: husking index, moisture content, paddy, rubber roll husker.

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Authors: Christian P. Crisostomo, Chrysline Margus N. Piñol

Abstract:

A zero-field ferromagnetic Ising model is utilized to simulate the propagation of infection in a population that assumes a square lattice structure. The rate of infection increases with temperature. The disease spreads faster among individuals with low J values. Such effect, however, diminishes at higher temperatures.

Keywords: Epidemiology, Ising model, lattice models

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Authors: H. M. Mohammad, A. Martin, N. Brown, N. Hodson, P. Hill, E. Roberts

Abstract:

Graphite intercalation compound (GIC) has been demonstrated to be a useful, low capacity and rapid adsorbent for the removal of organic micropollutants from water. The high electrical conductivity and low capacity of the material lends itself to electrochemical regeneration. Following electrochemical regeneration, equilibrium loading under similar conditions is reported to exceed that achieved by the fresh adsorbent. This behavior is reported in terms of the regeneration efficiency being greater than 100%. In this work, surface analysis techniques are employed to investigate the material in three states: ‘Fresh’, ‘Loaded’ and ‘Regenerated’. ‘Fresh’ GIC is shown to exhibit a hydrogen and oxygen rich surface layer approximately 150 nm thick. ‘Loaded’ GIC shows a similar but slightly thicker surface layer (approximately 370 nm thick) and significant enhancement in the hydrogen and oxygen abundance extending beyond 600 nm from the surface. 'Regenerated’ GIC shows an oxygen rich layer, slightly thicker than the fresh case at approximately 220 nm while showing a very much lower hydrogen enrichment at the surface. Results demonstrate that while the electrochemical regeneration effectively removes the phenol model pollutant, it also oxidizes the exposed carbon surface. These results may have a significant impact on the estimation of adsorbent life.

Keywords: Graphite, adsorbent, electrochemical, regeneration, phenol.

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Authors: Insung Jung, Gi-Nam Wang

Abstract:

In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

Abstract:

Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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Authors: Monday O. Ale, Adebukola A. Akintade, Olasunbo O. Orungbemi

Abstract:

Fermentation as an important operation in the processing of cocoa beans is now affected by the recent climate change across the globe. The major requirement for effective fermentation is the ability of the material used to retain sufficient heat for the required microbial activities. Apart from the effects of climate on the rate of heat retention, the materials used for fermentation plays an important role. Most Farmers still restrict fermentation activities to the use of traditional methods. Improving on cocoa fermentation in this era of climate change makes it necessary to work on other materials that can be suitable for cocoa fermentation. Therefore, the objective of this study was to determine the effects of fermentation techniques on the quality of cocoa beans. The materials used in this fermentation research were heap-leaves (traditional), stainless steel, plastic tin, plastic basket and wooden box. The period of fermentation varies from zero days to 10 days. Physical and chemical tests were carried out for variables in quality determination in the samples. The weight per bean varied from 1.0-1.2 g after drying across the samples and the major color of the dry beans observed was brown except with the samples from stainless steel. The moisture content varied from 5.5-7%. The mineral content and the heavy metals decreased with increase in the fermentation period. A wooden box can conclusively be used as an alternative to heap-leaves as there was no significant difference in the physical features of the samples fermented with the two methods. The use of a wooden box as an alternative for cocoa fermentation is therefore recommended for cocoa farmers.

Keywords: Effects, fermentation, fermentation materials, period, quality.

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Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

Abstract:

Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is widely used for LV segmentation, but it suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is improved to achieve a fast and efficient LV segmentation. First, a robust and efficient detection based on Hough forest localizes cardiac feature points. Such feature points are used to predict the initial fitting of the LV shape model. Second, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. With the robust initialization, ASM is able to achieve more accurate segmentation. The performance of the proposed method is evaluated on a dataset of 810 cardiac ultrasound images that are mostly abnormal shapes. This proposed method is compared with several combinations of ASM and existing initialization methods. Our experiment results demonstrate that accuracy of the proposed method for feature point detection for initialization was 40% higher than the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops and thus speeds up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: Hough forest, active shape model, segmentation, cardiac left ventricle.

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