Search results for: genetic breeding models

Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Lamis Naddaf, Yuval Tabach

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We identified missense genetic variants with the potential to enhance resistance against cancer. Such a field has not been widely explored as researchers tend to investigate the mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and have significant implications for improved risk estimation, diagnostics, prognosis, and even personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and selected the alleles that showed a correlation with the species’ cancer resistance. Interestingly, we found several amino acids that are more generally preferred (like the Proline) or avoided (like the Cysteine) by the resistant species. Furthermore, Cancer resistance in mammals and reptiles is significantly predicted by the number of the predicted protecting variants (PVs) a species has. Moreover, PVs-enriched-genes are enriched in pathways relevant to tumor suppression. For example, they are enriched in the Hedgehog signaling and silencing pathways, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are mostly more abundant in healthy people compared to cancer patients within different human races.

Keywords: cancer resistance, protecting variant, naked mole rat, comparative genomics

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Authors: V. Vargas-Alejo, L. E. Montero-Moguel

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Understanding the concept of function has been important in mathematics education for many years. In this study, the models built by a group of five business administration and accounting undergraduate students when carrying out a population growth activity are analyzed. The theoretical framework is the Models and Modeling Perspective. The results show how the students included tables, graphics, and algebraic representations in their models. Using technology was useful to interpret, describe, and predict the situation. The first model, the students built to describe the situation, was linear. After that, they modified and refined their ways of thinking; finally, they created exponential growth. Modeling the activity was useful to deep on mathematical concepts such as covariation, rate of change, and exponential function also to differentiate between linear and exponential growth.

Keywords: covariation reasoning, exponential function, modeling, representations

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Authors: Mayowa A. Sofowora, Seraphim D. Eyono Obono

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In recent times the level of advancement in electronics and manufacturing technologies for portable electronic devices, especially for mobile devices such as cell phones, smartphones, personal digital assistants and tablet computers is unprecedented. Mobile devices have become indispensable to individuals, and businesses all over the world. The high level of manufacturing and production of mobile devices has led to the rapid release of newer and sleeker models with new features and capabilities. However, these newer models therefore render older models obsolete, and this pushes people to frequently replace their devices. The drawback of such frequent replacements is that a large number of devices are disposed and they end up as e-waste. The fact that e-waste constitutes a major hazard to human health and to the environment is the motivation behind this study whose aim is to develop a model of possible factors that affects the dependability of mobile devices which in turn leads to the obsolescence of these devices.

Keywords: dependability, mobile devices, obsolescence, e-waste

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Authors: Ankush Kalra, Mirza Masroor, Usha Manaktala, B. C. Koner, T. K. Mishra

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Introduction: Pre-eclampsia affects 3-5% of pregnancies worldwide and increases maternal-fetal morbidity and mortality. Reduced placental perfusion induces the release of biomolecules by the placenta into maternal circulation causing endothelial dysfunction. Zinc dependent matrix metalloproteinase-2 (MMP-2) may be up-regulated and interact with circulating factors of oxidative stress and inflammation to produce endothelial dysfunction in pre-eclampsia. Aim: To study the functional genetic polymorphism of MMP-2 gene (g-1306 C>T) in pre-eclampsia and its effect on serum MMP-2 levels in these patients. Method: Hundred pre-eclampsia patients and hundred age and gestation period matched healthy pregnant women with their consent were recruited in the study. Serum MMP-2 levels in all subjects were estimated using standard ELISA kits. MMP-2 gene (g.- 1306 C>T) SNPs were genotyped using whole blood by ASO-PCR. Result: The pre-eclampsia patients had higher serum levels of MMP-2 compared to the healthy pregnant (p < 0.05). Also the MMP-2 genotype was associated with significant alteration in the serum MMP-2 concentration in these patients (p < 0.05). Conclusion: This study results suggest an association of MMP-2 genetic polymorphism and serum levels of MMP-2 to the path physiology of hypertensive disorder of pregnancy.

Keywords: allele specific oligonucleotide polymerase chain reaction (ASO-PCR), enzyme linked immunosorbent assay (ELISA), matrix metalloproteinase-2 (MMP-2), pre-eclampsia

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Authors: Haile Berihulay, Chenglong Luo

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Avian influenza, commonly known as bird flu, is a highly contagious viral disease primarily affecting poultry and wild birds, with significant implications for both animal health and public safety. The influenza virus (IV) is notorious for its ability to mutate and infect multiple species, including humans, leading to severe consequences. Avian influenza poses considerable pandemic risks due to the potential evolution of low pathogenic avian influenza (LPAI) into highly pathogenic avian influenza (HPAI), which can cause rapid outbreaks in domestic flocks. While AVI viruses typically do not replicate well in humans, strains such as H5N1 and H7N9 have crossed the species barrier, raising alarm over human infections. The recent documentation of human transmission of the H5N8 strain from birds underscores the ongoing threat posed by avian influenza. This review necessitates a thorough discussion about the genetic foundation of viral pathogens, identifying key candidate genes linked to disease resilience, and discussing powerful tools. This review can help researchers to comprehensively overview the disease severity and combat related to AIV, which causes significant economic impact and set effective control strategies to mitigate the risks associated with avian influenza outbreaks.

Keywords: Avian, candidate genes, chicken, molecular, pathogen, virus

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Authors: Alan S. Hoback

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Most people see human faces in car front and back ends because of the process of pareidolia. 96 people were surveyed to see how many of them saw a face in the vehicle styling. Participants were aged 18 to 72 years. 94% of the participants saw faces in the front-end design of production models. All participants that recognized faces indicated that most styles showed some degree of an angry expression. It was found that women were more likely to see faces in inanimate objects. However, with respect to whether women were more likely to perceive anger in the vehicle design, the results need further clarification. Survey responses were correlated to the design features of vehicles to determine what cues the respondents were likely looking at when responding. Whether the features looked anthropomorphic was key to anger perception. Features such as the headlights which could represent eyes and the air intake that could represent a mouth had high correlations to trends in scores. Results are compared among models, makers, by groupings of body styles classifications for the top 12 brands sold in the US, and by year for the top 20 models sold in the US in 2016. All of the top models sold increased in perception of an angry expression over the last 20 years or since the model was introduced, but the relative change varied by body style grouping.

Keywords: aggressive driving, face recognition, road rage, vehicle styling

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Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

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Graphical Human Interface, also known as supervision software, are increasingly present in industrial processes supported by Supervisory Control and Data Acquisition (SCADA) systems and so it is evident the need for qualified developers. In order to make engineering students able to produce high quality supervision software, method for the development must be created. In this paper we propose model, based on the international standards ISO/IEC 25010 and ISO/IEC 25040, for the development of graphical human interface. When compared with to other methods through experiments, the model here presented leads to improved quality indexes, therefore help guiding the decisions of programmers. Results show the efficiency of the models and the contribution to student learning. Students assessed the training they have received and considered it satisfactory.

Keywords: software development models, software quality, supervision software, fuzzy logic

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Authors: Harsh Thakkar, Ganesh Iyer

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In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

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Authors: Anchal Rana

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Indian Himalayas with their diverse climatic conditions are home to many rare and endangered medicinal flora. One such species is Polygonatum verticillatum Linn., popularly known as King Solomon’s Seal or Solomon’s Seal. Its mention as an incredible medicinal herb comes from 5000 years ago in Indian Materia Medica as a component of Ashtavarga, a poly-herbal formulation comprising of eight herbs illustrated as world’s first ever revitalizing and rejuvenating nutraceutical food, which is now commercialised in the name ‘Chaywanprash’. It is an erect tall (60 to 120 cm) perennial herb with sessile, linear leaves and white pendulous flowers. The species grows well in an altitude range of 1600 to 3600 m amsl, and propagates mostly through rhizomes. The rhizomes are potential source for significant phytochemicals like flavonoids, phenolics, lectins, terpenoids, allantoin, diosgenin, β-Sitosterol and quinine. The presence of such phytochemicals makes the species an asset for antioxidant, cardiotonic, demulcent, diuretic, energizer, emollient, aphrodisiac, appetizer, glactagogue, etc. properties. Having profound concentrations of macro and micronutrients, species has fine prospects of being used as a diet supplement. However, due to unscientific and gregarious uprooting, it has been assigned a status of ‘vulnerable’ and ‘endangered’ in the Conservation Assessment and Management Plan (CAMP) process conducted by Foundation for Revitalisation of Local Health Traditions (FRLHT) during 2010, according to IUCN Red-List Criteria. Further, destructive harvesting, land use disturbances, heavy livestock grazing, climatic changes and habitat fragmentation have substantially contributed towards anomaly of the species. It, therefore, became imperative to conserve the diversity of the species and make judicious use in future research and commercial programme and schemes. A Gene Bank was therefore established at High Altitude Herbal Garden of the Forest Research Institute, Dehradun, India situated at Chakarata (30042’52.99’’N, 77051’36.77’’E, 2205 m amsl) consisting 149 accessions collected from thirty-one geographical locations spread over three Himalayan States of Jammu and Kashmir, Himachal Pradesh, and Uttarakhand. The present investigations purport towards sampling and collection of divergent germplasm followed by planting and cultivation techniques. The ultimate aim is thereby focussed on analysing genetic diversity of the species and capturing promising genotypes for carrying out further genetic improvement programme so to contribute towards sustainable development and healthcare.

Keywords: Polygonatum verticillatum Linn., phytochemicals, genetic diversity, conservation, gene bank

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Authors: Mourad Ben Bennani

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Views of language and language learning have undergone a tremendous change over the last decades. Language is no longer seen as a set of structured rules. It is rather viewed as a tool of interaction and communication. This shift in views has resulted in change in viewing language learning, which gave birth to various approaches and methodologies of language teaching. Two of these approaches are content-based instruction and content and language integrated learning (CLIL). These are similar approaches which integrate content and foreign/second language learning through various methodologies and models as a result of different implementations around the world. This presentation deals with sociocultural view of CBI and CLIL. It also defines language and content as vital components of CBI and CLIL. Next it reviews the origins of CBI and the continuum perspectives and CLIL definitions and models featured in the literature. Finally it summarizes current aspects around research in program evaluation with a focus on the benefits and challenges of these innovative approaches for second language teaching.

Keywords: CBI, CLIL, CBI continuum, CLIL models

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Authors: Mabrouka Morri, Amel Soualmia, Philippe Belleudy

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Vegetation affects the mean and turbulent flow structure. It may increase flood risks and sediment transport. Therefore, it is important to develop analytical approaches for the bed shear stress on vegetated bed, to predict resistance caused by vegetation. In the recent years, experimental and numerical models have both been developed to model the effects of submerged vegetation on open-channel flow. In this paper, different analytic models are compared and tested using the criteria of deviation, to explore their capacity for predicting the mean velocity and select the suitable one that will be applied in real case of rivers. The comparison between the measured data in vegetated flume and simulated mean velocities indicated, a good performance, in the case of rigid vegetation, whereas, Huthoff model shows the best agreement with a high coefficient of determination (R2=80%) and the smallest error in the prediction of the average velocities.

Keywords: analytic models, comparison, mean velocity, vegetation

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Authors: Subir S. Rao

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Existing warehouse configurations use non-traditional aisle designs with a central P/D point in their models, which is mathematically simple but less practical. Many warehouses use multiple P/D points to avoid congestion for pickers, and different warehouses have different flow policies and infrastructure for using the P/D points. Many warehouses use multiple P/D points with non-traditional aisle designs in their analytical models. Standard warehouse models introduce one-sided multiple P/D points in a flying-V warehouse and minimize pick distance for a one-way travel between an active P/D point and a pick location with P/D points, assuming uniform flow rates. A simulation of the mathematical model generally uses four fixed configurations of P/D points which are on two different sides of the warehouse. It can be easily proved that if the source and destination P/D points are both chosen randomly, in a uniform way, then minimizing the one-way travel is the same as minimizing the two-way travel. Another warehouse configuration analytically models the warehouse for multiple one-sided P/D points while keeping the angle of the cross-aisles and picking aisles as a decision variable. The minimization of the one-way pick travel distance from the P/D point to the pick location by finding the optimal position/angle of the cross-aisle and picking aisle for warehouses having different numbers of multiple P/D points with variable flow rates is also one of the objectives. Most models of warehouses with multiple P/D points are one-way travel models and we extend these analytical models to minimize the two-way pick travel distance wherein the destination P/D is chosen optimally for the return route, which is not similar to minimizing the one-way travel. In most warehouse models, the return P/D is chosen randomly, but in our research, the return route P/D point is chosen optimally. Such warehouses are common in practice, where the flow rates at the P/D points are flexible and depend totally on the position of the picks. A good warehouse management system is efficient in consolidating orders over multiple P/D points in warehouses where the P/D is flexible in function. In the latter arrangement, pickers and shrink-wrap processes are not assigned to particular P/D points, which ultimately makes the P/D points more flexible and easy to use interchangeably for picking and deposits. The number of P/D points considered in this research uniformly increases from a single-central one to a maximum of each aisle symmetrically having a P/D point below it.

Keywords: non-traditional warehouse, V cross-aisle, multiple P/D point, pick travel distance

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Authors: Azadeh Jafari, Robert G. Owens

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In this study, a geometrical multiscale approach which means coupling together the 2-D Navier-Stokes equations, constitutive equations and 0-D lumped parameter models is investigated. A multiscale approach, suggest a natural way of coupling detailed local models (in the flow domain) with coarser models able to describe the dynamics over a large part or even the whole cardiovascular system at acceptable computational cost. In this study we introduce a new velocity correction scheme to decouple the velocity computation from the pressure one. To evaluate the capability of our new scheme, a comparison between the results obtained with Neumann outflow boundary conditions on the velocity and Dirichlet outflow boundary conditions on the pressure and those obtained using coupling with the lumped parameter model has been performed. Comprehensive studies have been done based on the sensitivity of numerical scheme to the initial conditions, elasticity and number of spectral modes. Improvement of the computational algorithm with stable convergence has been demonstrated for at least moderate Weissenberg number. We comment on mathematical properties of the reduced model, its limitations in yielding realistic and accurate numerical simulations, and its contribution to a better understanding of microvascular blood flow. We discuss the sophistication and reliability of multiscale models for computing correct boundary conditions at the outflow boundaries of a section of the cardiovascular system of interest. In this respect the geometrical multiscale approach can be regarded as a new method for solving a class of biofluids problems, whose application goes significantly beyond the one addressed in this work.

Keywords: geometrical multiscale models, haemorheology model, coupled 2-D navier-stokes 0-D lumped parameter modeling, computational fluid dynamics

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Authors: Jean Pierre Kabue, Emma Meader, Afsatou Ndama Traore, Paul R. Hunter, Natasha Potgieter

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Norovirus is now considered the most common cause of outbreaks of nonbacterial gastroenteritis. Limited data are available for Norovirus strains in Africa, especially in rural and peri-urban areas. Despite the excessive burden of diarrhea disease in developing countries, Norovirus infections have been to date mostly reported in developed countries. There is a need to investigate intensively the role of viral agents associated with diarrhea in different settings in Africa continent. To determine the prevalence and genetic diversity of Norovirus strains circulating in the rural communities in the Limpopo Province, South Africa and investigate the genetic relationship between Norovirus strains, a cross-sectional study was performed on human stools collected from rural communities. Between July 2014 and April 2015, outpatient children under 5 years of age from rural communities of Vhembe District, South Africa, were recorded for the study. A total of 303 stool specimens were collected from those with diarrhea (n=253) and without (n=50) diarrhea. NoVs were identified using real-time one-step RT-PCR. Partial Sequence analyses were performed to genotype the strains. Phylogenetic analyses were performed to compare identified NoVs genotypes to the worldwide circulating strains. Norovirus detection rate was 41.1% (104/253) in children with diarrhea. There was no significant difference (OR=1.24; 95% CI 0.66-2.33) in Norovirus detection between symptomatic and asymptomatic children. Comparison of the median CT values for NoV in children with diarrhea and without diarrhea revealed significant statistical difference of estimated GII viral load from both groups, with a much higher viral burden in children with diarrhea. To our knowledge, this is the first study reporting on the differences in estimated viral load of GII and GI NoV positive cases and controls. GII.Pe (n=9) were the predominant genotypes followed by GII.Pe/GII.4 Sydney 2012 (n=8) suspected recombinant and GII.4 Sydney 2012 variants(n=7). Two unassigned GII.4 variants and an unusual RdRp genotype GII.P15 were found. With note, the rare GIIP15 identified in this study has a common ancestor with GIIP15 strain from Japan previously reported as GII/untypeable recombinant strain implicated in a gastroenteritis outbreak. To our knowledge, this is the first report of this unusual genotype in the African continent. Though not confirmed predictive of diarrhea disease in this study, the high detection rate of NoV is an indication of subsequent exposure of children from rural communities to enteric pathogens due to poor sanitation and hygiene practices. The results reveal that the difference between asymptomatic and symptomatic children with NoV may possibly be related to the NoV genogroups involved. The findings emphasize NoV genetic diversity and predominance of GII.Pe/GII.4 Sydney 2012, indicative of increased NoV activity. An uncommon GII.P15 and two unassigned GII.4 variants were also identified from rural settings of the Vhembe District/South Africa. NoV surveillance is required to help to inform investigations into NoV evolution, and to support vaccine development programmes in Africa.

Keywords: asymptomatic, common, outpatients, norovirus genetic diversity, sporadic gastroenteritis, South African rural communities, symptomatic

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Authors: Zhihan Li

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Nowadays, most universities use the course enrollment system considering students’ registration orders. However, the students’ preference level to certain courses is also one important factor to consider. In this research, the possibility of applying a preference-first system has been discussed and analyzed compared to the order-first system. A bipartite graph is applied to resemble the relationship between students and courses they tend to register. With the graph set up, we apply Ford-Fulkerson (F.F.) Algorithm to maximize parings between two sets of nodes, in our case, students and courses. Two models are proposed in this paper: the one considered students’ order first, and the one considered students’ preference first. By comparing and contrasting the two models, we highlight the usability of models which potentially leads to better designs for school course registration systems.

Keywords: bipartite graph, Ford-Fulkerson (F.F.) algorithm, graph theory, maximum matching

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Authors: Nikolett Deutsch, Éva Pintér, Péter Bagó, Miklós Hetényi

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Strategic technology management has emerged and evolved parallelly with strategic management paradigms. It focuses on the opportunity for organizations operating mainly in technology-intensive industries to explore and exploit technological capabilities upon which competitive advantage can be obtained. As strategic technology management involves multifunction within an organization, requires broad and diversified knowledge, and must be developed and implemented with business objectives to enable a firm’s profitability and growth, excellence in strategic technology management provides unique opportunities for organizations in terms of building a successful future. Accordingly, a framework supporting the evaluation of the technological readiness level of management can significantly contribute to developing organizational competitiveness through a better understanding of strategic-level capabilities and deficiencies in operations. In the last decade, several innovation maturity assessment models have appeared and become designated management tools that can serve as references for future practical approaches expected to be used by corporate leaders, strategists, and technology managers to understand and manage technological capabilities and capacities. The aim of this paper is to provide a comprehensive review of the state-of-the-art innovation maturity frameworks, to investigate the critical lessons learned from their application, to identify the similarities and differences among the models, and identify the main aspects and elements valid for the field and critical functions of technology management. To this end, a systematic literature review was carried out considering the relevant papers and articles published in highly ranked international journals around the 27 most widely known innovation maturity models from four relevant digital sources. Key findings suggest that despite the diversity of the given models, there is still room for improvement regarding the common understanding of innovation typologies, the full coverage of innovation capabilities, and the generalist approach to the validation and practical applicability of the structure and content of the models. Furthermore, the paper proposes an initial structure by considering the maturity assessment of the technological capacities and capabilities - i.e., technology identification, technology selection, technology acquisition, technology exploitation, and technology protection - covered by strategic technology management.

Keywords: innovation capabilities, innovation maturity models, technology audit, technology management, technology management maturity models

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Authors: Hieu Van Dong, Giang Thi Huong Tran, Giap Van Nguyen, Tung Duy Dao, Vuong Nghia Bui, Le Thi My Huynh, Yohei Takeda, Haruko Ogawa, Kunitoshi Imai

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Chicken anemia virus (CAV) has a ubiquitous and worldwide distribution in chicken production. Our group previously reported high seroprevalence of CAV in chickens in northern Vietnam. In the present study, 330 tissue samples collected from commercial and breeder chicken farms in eleven provinces in northern Vietnam were tested for the CAV infection. We found that 157 out of 330 (47.58%) chickens were positive with CAV genes by real-time PCR method. Nine CAV strains obtained from the different location and time were forwarded to the full-length sequence of CAV VP1 gene. Phylogenetic analysis of the Vietnamese CAV vp1 gene indicated that the CAVs circulating in northern Vietnam were divided into three distinct genotypes, II, III, and V, but not clustered with the vaccine strains. Among the three genotypes, genotype III was the major one widely spread in Vietnam, and that included three sub-genotypes, IIIa, IIIb, and IIIc. The Vietnamese CAV strains were closely related to the Chinese, Taiwanese, and USA strains. All the CAV isolates had glutamine at amino acid position 394 in the VP1 gene, suggesting that they might be highly pathogenic strains. One strain was defined to be genotype V, which had not been reported for Vietnamese CAVs. Additional studies are required to further evaluate the pathogenicity of CAV strains circulating in Vietnam.

Keywords: chicken anemia virus, genotype, genetic characteristics, Vietnam

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Authors: Stephanie A. Schauder, Gosia Sylwestrzak

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Overweight and obese women report avoiding preventive care due to fear of weight-related bias from medical professionals. Gynecological exams, due to their sensitive and personally invasive nature, are especially susceptible to avoidance. This research investigates the association between body mass index (BMI) and screening rates for breast and cervical cancer using claims data from 1.3 million members of a large health insurance company. Because obesity is associated with increased cancer risk, screenings for these cancers should increase as BMI increases. However, this paper finds that the distribution of cancer screening rates by BMI take an inverted U-shape with underweight and obese members having the lowest screening rates. For cervical cancer screening, those in the target population with a BMI of 23 have the highest screening rate at 68%, while Obese Class III members have a screening rate of 50%. Those in the underweight category have a screening rate of 58%. This relationship persists even after controlling for health and demographic covariates in regression analysis. Interestingly, there is no association between BMI and BRCA (BReast CAncer gene) genetic testing. This is consistent with the narrative that stigma causes avoidance because genetic testing does not involve any assessment of a person’s body. More work must be done to determine how to increase cancer screening rates in those who may feel stigmatized due to their weight.

Keywords: cancer screening, cervical cancer, breast cancer, weight stigma, avoidance of care

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Authors: Mohamed S. Sasi, Adel M. Mlitan, Abdulfattah M. Alkherraz

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This research project aims to investigate difference in relative rates concerning phosphoryl transfer relevant to biological catalysis of DNA and RNA in the pH-independent reactions. Activated Models of DNA and RNA for alkyl-aryl phosphate diesters (with 4-nitrophenyl as a good leaving group) have successfully been prepared to gather kinetic parameters. Eyring plots for the pH–independent hydrolysis of 1 and 2 were established at different temperatures in the range 100–160 °C. These measurements have been used to provide a better estimate for the difference in relative rates between the reactivity of DNA and RNA cleavage. Eyring plot gave an extrapolated rate of kH2O = 1 × 10-10 s -1 for 1 (RNA model) and 2 (DNA model) at 25°C. Comparing the reactivity of RNA model and DNA model shows that the difference in relative rates in the pH-independent reactions is surprisingly very similar at 25°. This allows us to obtain chemical insights into how biological catalysts such as enzymes may have evolved to perform their current functions.

Keywords: DNA and RNA models, relative rates, reactivity, phosphoryl transfe

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Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: Murray David Schane

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Though years of clinical encounters with patients with autism spectrum disorders and those with a schizoid personality the many defining diagnostic features shared between these conditions have been explored and current neurobiological differences have been reviewed; and, critical and different treatment strategies for each have been devised. The paper compares and contrasts the apparent similarities between autism spectrum disorders and the schizoid personality are found in these DSM descriptive categories: restricted range of social-emotional reciprocity; poor non-verbal communicative behavior in social interactions; difficulty developing and maintaining relationships; detachment from social relationships; lack of the desire for or enjoyment of close relationships; and preference for solitary activities. In this paper autism, fundamentally a communicative disorder, is revealed to present clinically as a pervasive aversive response to efforts to engage with or be engaged by others. Autists with the Asperger presentation typically have language but have difficulty understanding humor, irony, sarcasm, metaphoric speech, and even narratives about social relationships. They also tend to seek sameness, possibly to avoid problems of social interpretation. Repetitive behaviors engage many autists as a screen against ambient noise, social activity, and challenging interactions. Also in this paper, the schizoid personality is revealed as a pattern of social avoidance, self-sufficiency and apparent indifference to others as a complex psychological defense against a deep, long-abiding fear of appropriation and perverse manipulation. Neither genetic nor MRI studies have yet located the explanatory data that identifies the cause or the neurobiology of autism. Similarly, studies of the schizoid have yet to group that condition with those found in schizophrenia. Through presentations of clinical examples, the treatment of autists of the Asperger type is revealed to address the autist’s extreme social aversion which also precludes the experience of empathy. Autists will be revealed as forming social attachments but without the capacity to interact with mutual concern. Empathy will be shown be teachable and, as social avoidance relents, understanding of the meaning and signs of empathic needs that autists can recognize and acknowledge. Treatment of schizoids will be shown to revolve around joining empathically with the schizoid’s apprehensions about interpersonal, interactive proximity. Models of both autism and schizoid personality traits have yet to be replicated in animals, thereby eliminating the role of translational research in providing the kind of clues to behavioral patterns that can be related to genetic, epigenetic and neurobiological measures. But as these clinical examples will attest, treatment strategies have significant impact.

Keywords: autism spectrum, schizoid personality traits, neurobiological implications, critical diagnostic distinctions

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Authors: Elfatih M. Abdel-Rahman, Tobias Landmann, Richard Kyalo, George Ong’amo, Bruno Le Ru

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Maize (Zea mays L.) is a major staple food crop in Africa, particularly in the eastern region of the continent. The maize growing area in Africa spans over 25 million ha and 84% of rural households in Africa cultivate maize mainly as a means to generate food and income. Average maize yields in Sub Saharan Africa are 1.4 t/ha as compared to global average of 2.5–3.9 t/ha due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In East Africa, yield losses due to stem borers are currently estimated between 12% to 40% of the total production. The objective of the present study was therefore to predict stem borer larvae density in maize fields using RapidEye reflectance data and generalized linear models (GLMs). RapidEye images were captured for a test site in Kenya (Machakos) in January and in February 2015. Stem borer larva numbers were modeled using GLMs assuming Poisson (Po) and negative binomial (NB) distributions with error with log arithmetic link. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were employed to assess the models performance using a leave one-out cross-validation approach. Results showed that NB models outperformed Po ones in all study sites. RMSE and RPD ranged between 0.95 and 2.70, and between 2.39 and 6.81, respectively. Overall, all models performed similar when used the January and the February image data. We conclude that reflectance data from RapidEye data can be used to estimate stem borer larvae density. The developed models could to improve decision making regarding controlling maize stem borers using various integrated pest management (IPM) protocols.

Keywords: maize, stem borers, density, RapidEye, GLM

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Authors: Kelsi Hagerty, Ami Rosen, Aaliyah Heyward, Nadia Ali, Emily Brown, Erin Demo, Yue Guan, Modele Ogunniyi, Brianna McDaniels, Alanna Morris, Kunal Bhatt

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Hereditary transthyretin amyloidosis (hATTR) is a progressive, multi-systemic, and life-threatening disease caused by a disruption in the TTR protein that delivers thyroxine and retinol to the liver. This disruption causes the protein to misfold into amyloid fibrils, leading to the accumulation of the amyloid fibrils in the heart, nerves, and GI tract. Over 130 variants in the TTR gene are known to cause hATTR. The Val122Ile variant is the most common in the United States and is seen almost exclusively in people of African descent. TTR variants are inherited in an autosomal dominant fashion and have incomplete penetrance and variable expressivity. Individuals with hATTR may exhibit symptoms from as early as 30 years to as late as 80 years of age. hATTR is characterized by a wide range of clinical symptoms such as cardiomyopathy, neuropathy, carpal tunnel syndrome, and GI complications. Without treatment, hATTR leads to progressive disease and can ultimately lead to heart failure. hATTR disproportionately affects individuals of African descent; the estimated prevalence of hATTR among Black individuals in the US is 3.4%. Unfortunately, hATTR is often underdiagnosed and misdiagnosed because many symptoms of the disease overlap with other cardiac conditions. Due to the progressive nature of the disease, multi-systemic manifestations that can lead to a shortened lifespan, and the availability of free genetic testing and promising FDA-approved therapies that enhance treatability, early identification of individuals with a pathogenic hATTR variant is important, as this can significantly impact medical management for patients and their relatives. Furthermore, recent literature suggests that TTR genetic testing should be performed in all patients with suspicion of TTR-related cardiomyopathy, regardless of age, and that follow-up with genetic counseling services is recommended. Relatives of patients with hATTR benefit from genetic testing because testing can identify carriers early and allow relatives to receive regular screening and management. Despite the striking prevalence of hATTR among Black individuals, hATTR remains underdiagnosed in this patient population, and germline genetic testing for hATTR in Black individuals seems to be underrepresented, though the reasons for this have not yet been brought to light. Historically, Black patients experience a number of barriers to seeking healthcare that has been hypothesized to perpetuate the underdiagnosis of hATTR, such as lack of access and mistrust of healthcare professionals. Prior research has described a myriad of factors that shape an individual’s decision about whether to pursue presymptomatic genetic testing for a familial pathogenic variant, such as family closeness and communication, family dynamics, and a desire to inform other family members about potential health risks. This study explores these factors through 10 in-depth interviews with patients with hATTR about what factors may be contributing to the underdiagnosis of hATTR in the Black population. Participants were selected from the Emory University Amyloidosis clinic based on having a molecular diagnosis of hATTR. Interviews were recorded and transcribed verbatim, then coded using MAXQDA software. Thematic analysis was completed to draw commonalities between participants. Upon preliminary analysis, several themes have emerged. Barriers identified include i) Misdiagnosis and a prolonged diagnostic odyssey, ii) Family communication and dynamics surrounding health issues, iii) Perceptions of healthcare and one’s own health risks, and iv) The need for more intimate provider-patient relationships and communication. Overall, this study gleaned valuable insight from members of the Black community about possible factors contributing to the underdiagnosis of hATTR, as well as potential solutions to go about resolving this issue.

Keywords: cardiac amyloidosis, heart failure, TTR, genetic testing

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Authors: Shaomei Li, Yawen Wang, Chao Gao

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To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as a binary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm cannot only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Keywords: object tracking, tracking drift, partial least squares analysis, positive and negative models matching

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Authors: Palash Dey, Sudip Talukdar

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In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

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Authors: Baeza S. Roberto

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The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes are included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: neural network, dry relaxation, knitting, linear regression

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Authors: Natalia Koltovaya, Nadezhda Zhuchkina, Ksenia Lyubimova

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We study the biological effects induced by ionizing radiation in view of therapeutic exposure and the idea of space flights beyond Earth's magnetosphere. In particular, we examine the differences between base pair substitution induction by ionizing radiation in model haploid and diploid yeast Saccharomyces cerevisiae cells. Such mutations are difficult to study in higher eukaryotic systems. In our research, we have used a collection of six isogenic trp5-strains and 14 isogenic haploid and diploid cyc1-strains that are specific markers of all possible base-pair substitutions. These strains differ from each other only in single base substitutions within codon-50 of the trp5 gene or codon-22 of the cyc1 gene. Different mutation spectra for two different haploid genetic trp5- and cyc1-assays and different mutation spectra for the same genetic cyc1-system in cells with different ploidy — haploid and diploid — have been obtained. It was linear function for dose-dependence in haploid and exponential in diploid cells. We suggest that the differences between haploid yeast strains reflect the dependence on the sequence context, while the differences between haploid and diploid strains reflect the different molecular mechanisms of mutations.

Keywords: base pair substitutions, γ-rays, haploid and diploid cells, yeast Saccharomyces cerevisiae

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Authors: Danny Barash

Abstract:

Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

Procedia PDF Downloads 234