Search results for: vector diversity
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2776

Search results for: vector diversity

1006 Association of Major Histocompatibility Complex Alleles with Antibody Response to Newcastle Vaccine in Chicken

Authors: Atefeh Esmailnejad, Gholam Reza Nikbakht Brujeni

Abstract:

The major histocompatibility complex (MHC) is the best-characterized genetic region associated with susceptibility and/or resistance to a wide range of infectious diseases, autoimmune diseases and immune responses to vaccines. It has been demonstrated that there is an association between the MHC and resistance to Marek disease, Newcastle disease, Rous sarcoma tumor, Avian leucosis, Fowl cholera, Salmonellosis and Pasteurellosis in chicken. The present study evaluated the MHC polymorphism and its association with antibody response to Newcastle (ND) vaccine in Iranian native chickens. The MHC polymorphism was investigated using LEI0258 microsatellite locus by PCR-based fragment analysis. LEI0258 microsatellite marker is a genetic indicator for MHC, which is located on microchromosome 16 and strongly associated with serologically defined MHC haplotypes. Antibody titer against ND vaccine was measured by Haemaglutination Inhibition (HI) assay. Statistical analysis was performed using SPSS software (version 21). Total of 13 LEI0258 microsatellite alleles were identified in 72 samples which indicated a high genetic diversity in the population. The association study revealed a significant influence of MHC alleles on immune responses to Newcastle vaccine. 311 and 313 bp alleles were significantly associated with elevated immune responses to Newcastle vaccine (p<0.05). These results would be applicable in designing and improving the populations under selective breeding.

Keywords: chicken, LEI0258, MHC, Newcastle vaccine

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1005 Woman, House, Identity: The Study of the Role of House in Constructing the Contemporary Dong Minority Woman’s Identity

Authors: Sze Wai Veera Fung, Peter W. Ferretto

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Similar to most ethnic groups in China, men of the Dong minority hold the primary position in policymaking, moral authority, social values, and the control of the property. As the spatial embodiment of the patriarchal ideals, the house plays a significant role in producing and reproducing the distinctive gender status within the Dong society. Nevertheless, Dong women do not see their home as a cage of confinement, nor do they see themselves as a victim of oppression. For these women with reference to their productive identity, a house is a dwelling place with manifold meanings, including a proof of identity, an economic instrument, and a public resource operating on the community level. This paper examines the role of the house as a central site for identity construction and maintenance for the southern dialect Dong minority women in Hunan, China. Drawing on recent interviews with the Dong women, this study argues that women as productive individuals have a strong influence on the form of their house and the immediate environment, regardless of the male-dominated social construct of the Dong society. The aim of this study is not to produce a definitive relationship between women, house, and identity. Rather, it seeks to offer an alternative lens into the complexity and diversity of gender dynamics operating in and beyond the boundary of the house in the context of contemporary rural China.

Keywords: conception of home, Dong minority, house, rural China, woman’s identity

Procedia PDF Downloads 118
1004 Preparation and Characterization of Chitosan Nanoparticles for Delivery of Oligonucleotides

Authors: Gyati Shilakari Asthana, Abhay Asthana, Dharm Veer Kohli, Suresh Prasad Vyas

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Purpose: The therapeutic potential of oligonucleotide (ODN) is primarily dependent upon its safe and efficient delivery to specific cells overcoming degradation and maximizing cellular uptake in vivo. The present study is focused to design low molecular weight chitosan nanoconstructs to meet the requirements of safe and effectual delivery of ODNs. LMW-chitosan is a biodegradable, water soluble, biocompatible polymer and is useful as a non-viral vector for gene delivery due to its better stability in water. Methods: LMW chitosan ODN nanoparticles (CHODN NPs) were formulated by self-assembled method using various N/P ratios (moles ratio of amine groups of CH to phosphate moieties of ODNs; 0.5:1, 1:1, 3:1, 5:1, and 7:1) of CH to ODN. The developed CHODN NPs were evaluated with respect to gel retardation assay, particle size, zeta potential and cytotoxicity and transfection efficiency. Results: Complete complexation of CH/ODN was achieved at the charge ratio of 0.5:1 or above and CHODN NPs displayed resistance against DNase I. On increasing the N/P ratio of CH/ODN, the particle size of the NPs decreased whereas zeta potential (ZV) value increased. No significant toxicity was observed at all CH concentrations. The transfection efficiency was increased on increasing N/P ratio from 1:1 to 3:1, whereas it was decreased with further increment in N/P ratio upto 7:1. Maximum transfection of CHODN NPs with both the cell lines (Raw 267.4 cells and Hela cells) was achieved at N/P ratio of 3:1. The results suggest that transfection efficiency of CHODN NPs is dependent on N/P ratio. Conclusion: Thus the present study states that LMW chitosan nanoparticulate carriers would be acceptable choice to improve transfection efficiency in vitro as well as in vivo delivery of oligonucleotide.

Keywords: LMW-chitosan, chitosan nanoparticles, biocompatibility, cytotoxicity study, transfection efficiency, oligonucleotide

Procedia PDF Downloads 832
1003 Fake News Detection Based on Fusion of Domain Knowledge and Expert Knowledge

Authors: Yulan Wu

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The spread of fake news on social media has posed significant societal harm to the public and the nation, with its threats spanning various domains, including politics, economics, health, and more. News on social media often covers multiple domains, and existing models studied by researchers and relevant organizations often perform well on datasets from a single domain. However, when these methods are applied to social platforms with news spanning multiple domains, their performance significantly deteriorates. Existing research has attempted to enhance the detection performance of multi-domain datasets by adding single-domain labels to the data. However, these methods overlook the fact that a news article typically belongs to multiple domains, leading to the loss of domain knowledge information contained within the news text. To address this issue, research has found that news records in different domains often use different vocabularies to describe their content. In this paper, we propose a fake news detection framework that combines domain knowledge and expert knowledge. Firstly, it utilizes an unsupervised domain discovery module to generate a low-dimensional vector for each news article, representing domain embeddings, which can retain multi-domain knowledge of the news content. Then, a feature extraction module uses the domain embeddings discovered through unsupervised domain knowledge to guide multiple experts in extracting news knowledge for the total feature representation. Finally, a classifier is used to determine whether the news is fake or not. Experiments show that this approach can improve multi-domain fake news detection performance while reducing the cost of manually labeling domain labels.

Keywords: fake news, deep learning, natural language processing, multiple domains

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1002 Language Rights and the Challenge of National Integration: The Nigerian Experience

Authors: Odewumi Olatunde, Adegun Sunday

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Linguistic diversity is seen to complicate attempts to build a stable and cohesive political community. Hence, the challenge of integration is enormous in a multi-ethno-lingual country like Nigeria. In the same vein, justification for minority language rights claims in relation to broader political theories of justice, freedom and democracy cannot be ignored. It is in the light of the fore-going that this paper explores Nigeria’s experiments at language policy and planning(LPP) and the long drawn agitations for self-determination and linguistic freedom by the minority ethnic groups in the polity which has been exacerbated by the National Policy on Education language provisions. The paper succinctly reviews Nigeria’s LPP efforts and its attendant theater of conflicts; explores international attempts at evolving normative principles of freedom and equality for language policy and finally evaluates the position of the Nigerian LPP in the light of evolving international conventions. On this premise, it is concluded that giving a conscientious and honest implementation of the Nigerian language provisions as assessed from their face validity, the nation’s efforts could be exonerated from running afoul of any known civilized values and best practices. It is, therefore, recommended that an effectual and consistent commitment to implementation driven by a renewed political will is what is required for the nation to succeed in this direction.

Keywords: integration, rights, challenge, conventions, policy

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1001 Nutrition of Preschool Children in the Aspect of Nutritional Status

Authors: Klaudia Tomala, Elzbieta Grochowska-Niedworok, Katarzyna Brukalo, Marek Kardas, Beata Calyniuk, Renata Polaniak

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Background. Nutrition plays an important role in the psychophysical growth of children and has effects on their health. Providing children with the appropriate supply of macro- and micro-nutrients requires dietary diversity across every food group. Meals in kindergartens should provide 70-75% of their daily food requirement. Aim. The aim of this study was to determine the vitamin content in the food rations of children attending kindergarten in the wider aspect of nutritional status. Material and Methods. Kindergarten menus from the spring and autumn seasons of 2015 were analyzed. In these meals, fat content and levels of water-soluble vitamins were estimated. The vitamin content was evaluated using the diet calculator “Aliant”. Statistical analysis was done in MS Office Excel 2007. Results. Vitamin content in the analyzed menus in many cases is too high with reference to dietary intake, with only vitamin D intake being insufficient. Vitamin E intake was closest to the dietary reference intake. Conclusion. The results show that vitamin intake is usually too high, and menus should, therefore, be modified. Also, nutrition education among kindergarten staff is needed. The identified errors in the composition of meals will affect the nutritional status of children and their proper composition in the body.

Keywords: children, nutrition status, vitamins, preschool

Procedia PDF Downloads 144
1000 The Folksongs of Jharkhand: An Intangible Cultural Heritage of Tribal India

Authors: Walter Beck

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Jharkhand is newly constituted 28th State in the eastern part of India which is known for the oldest settlement of the indigenous people. In the State of Jharkhand in which broadly three language family are found namely, Austric, Dravidian, and Indo-European. Ex-Mundari, kharia, Ho Santali come from the Austric Language family. Kurukh, Malto under Dravidian language family and Nagpuri Khorta etc. under Indo-European language family. There are 32 Indigenous Communities identified as Scheduled Tribe in the State of Jharkhand. Santhal, Munda, Kahria, Ho and Oraons are some of the major Tribe of the Jharkhand state. Jharkhand has a Rich Cultural heritage which includes Folk art, folklore, Folk Dance, Folk Music, Folk Songs for which diversity can been seen from place to place, season to season and all traditional Culture and practices. The languages as well as the songs are vulnerable to dominant culture and hence needed to be protected. The collection and documentation of these songs in their natural setting adds significant contribution to the conservation and propagation of the cultural elements. This paper reflects to bring out the Originality of the Collected Songs from remote areas of the plateau of Sothern Jharkhand as a rich intangible Cultural heritage of the Country. The research was done through participatory observation. In this research project more than 100 songs which were never documented before.

Keywords: cultural heritage, India, indigenous people, songs, languages

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999 Characterization of Fateh Sagar Wetland and Its Catchment Area at Udaipur City, (Raj.) India, Using High Resolution Data

Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

Procedia PDF Downloads 382
998 Genetic Identification of Crop Cultivars Using Barcode System

Authors: Kesavan Markkandan, Ha Young Park, Seung-Il Yoo, Sin-Gi Park, Junhyung Park

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For genetic identification of crop cultivars, insertions/deletions (InDel) markers have been preferred currently because they are easy to use, PCR based, co-dominant and relatively abundant. However, new InDels need to be developed for genetic studies of new varieties due to the difference of allele frequencies in InDels among the population groups. These new varieties are evolved with low levels of genetic diversity in specific genome loci with high recombination rate. In this study, we described soybean barcode system approach based on InDel makers, each of which is specific to a variation block (VB), where the genomes split by all assumed recombination sites. Firstly, VBs in crop cultivars were mined for transferability to VB-specific InDel markers. Secondly, putative InDels in the VB regions were identified for the development of barcode system by analyzing particular cultivar’s whole genome data. Thirdly, common VB-specific InDels from all cultivars were selected by gel electrophoresis, which were converted as 2D barcode types according to comparing amplicon polymorphisms in the five cultivars to the reference cultivar. Finally, the polymorphism of the selected markers was assessed with other cultivars, and the barcode system that allows a clear distinction among those cultivars is described. The same approach can be applicable for other commercial crops. Hence, VB-based genetic identification not only minimize the molecular markers but also useful for assessing cultivars and for marker-assisted breeding in other crop species.

Keywords: variation block, polymorphism, InDel marker, genetic identification

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997 The Effects of Architectural Anatomy on Improving the Quality of Place Identity: Case Study of Shiraz Opera Hall

Authors: Hamid Reza Zeraatpisheh, Shamsoddin Hashemi, Farshad Negintaji

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This study has examined the effects of the architectural anatomy of opera hall on improving the quality of place identity. By measuring the effects of place identity on the inner aspects of human which are influenced by the physical and social environments it has investigated the results of a balance between internal and external environment. To assess the anatomical effects of urban landscape, two components of subjective landscape including perception and diversity and the component of objective landscape including form and order have been measured. The current survey is descriptive and the statistical population has been Shiraz which is a city in Iran. To analyze the data the SPSS software has been used. The results have been investigated in two levels of descriptive and inferential statistics. In the inferential statistics, Pearson correlation coefficient has been used to evaluate the research hypotheses. The results of this study indicate that between the dimensions of landscape, the component of the subjective landscape has the highest impact on the place identity and in the second place, an objective landscape has the impact on the place identity. Anatomical effects have an important role on improving the quality of place identity of Shiraz citizens and in order to enhance the place identity in the urban landscape it is also required that they will be inspired and operated.

Keywords: architectural anatomy, identity, place identity, urban landscape, perception

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996 Land Cover Remote Sensing Classification Advanced Neural Networks Supervised Learning

Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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995 FT-NIR Method to Determine Moisture in Gluten Free Rice-Based Pasta during Drying

Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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994 Enhancement Method of Network Traffic Anomaly Detection Model Based on Adversarial Training With Category Tags

Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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993 Designing a Smart City Relying on Renewable Energies: A Solution in the Concept of Sustainable Development

Authors: Mina Bakhshi

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Nowadays, issues such as various types of pollution, problems caused by energy consumption, population density, social activities, difficulties related to urban access and communication, transportation, etc., have challenged different communities and become the subject of their discussions. In response to this issue, theories and movements have emerged to achieve sustainable urban development, including the smart growth movement. This theory emphasizes that the physical growth and expansion of cities should serve the community and the environment, aiming to improve the quality of life and promote the use of renewable energy resources for sustainability. The smart city network system not only improves the economic situation of the society and benefits the environment but also enables the achievement of important issues such as sustainable development, continuity, and diversity of energy resources. In this article, we investigate the impact of using renewable energy sources on optimizing energy consumption and reducing pollution caused by fossil fuels with the help of smart city development. The aim of this article is to introduce renewable energy sources and their utilization as a solution to address the energy crisis and reduce environmental pollution. This research has attempted to introduce the smart city and the use of renewable energy sources as a method for solving many urban problems and achieving efficient urban control and management.

Keywords: smart city, renewable energy sources, sustainable development, sustainable city

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992 Reducing the Imbalance Penalty Through Artificial Intelligence Methods Geothermal Production Forecasting: A Case Study for Turkey

Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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991 Economic Growth: The Nexus of Oil Price Volatility and Renewable Energy Resources among Selected Developed and Developing Economies

Authors: Muhammad Siddique, Volodymyr Lugovskyy

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This paper explores how nations might mitigate the unfavorable impacts of oil price volatility on economic growth by switching to renewable energy sources. The impacts of uncertain factor prices on economic activity are examined by looking at the Realized Volatility (RV) of oil prices rather than the more traditional method of looking at oil price shocks. The United States of America (USA), China (C), India (I), United Kingdom (UK), Germany (G), Malaysia (M), and Pakistan (P) are all included to round out the traditional literature's examination of selected nations, which focuses on oil-importing and exporting economies. Granger Causality Tests (GCT), Impulse Response Functions (IRF), and Variance Decompositions (VD) demonstrate that in a Vector Auto-Regressive (VAR) scenario, the negative impacts of oil price volatility extend beyond what can be explained by oil price shocks alone for all of the nations in the sample. Different nations have different levels of vulnerability to changes in oil prices and other factors that may play a role in a sectoral composition and the energy mix. The conventional method, which only takes into account whether a country is a net oil importer or exporter, is inadequate. The potential economic advantages of initiatives to decouple the macroeconomy from volatile commodities markets are shown through simulations of volatility shocks in alternative energy mixes (with greater proportions of renewables). It is determined that in developing countries like Pakistan, increasing the use of renewable energy sources might lessen an economy's sensitivity to changes in oil prices; nonetheless, a country-specific study is required to identify particular policy actions. In sum, the research provides an innovative justification for mitigating economic growth's dependence on stable oil prices in our sample countries.

Keywords: oil price volatility, renewable energy, economic growth, developed and developing economies

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990 Genomic Diversity and Relationship among Arabian Peninsula Dromedary Camels Using Full Genome Sequencing Approach

Authors: H. Bahbahani, H. Musa, F. Al Mathen

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The dromedary camels (Camelus dromedarius) are single-humped even-toed ungulates populating the African Sahara, Arabian Peninsula, and Southwest Asia. The genome of this desert-adapted species has been minimally investigated using autosomal microsatellite and mitochondrial DNA markers. In this study, the genomes of 33 dromedary camel samples from different parts of the Arabian Peninsula were sequenced using Illumina Next Generation Sequencing (NGS) platform. These data were combined with Genotyping-by-Sequencing (GBS) data from African (Sudanese) dromedaries to investigate the genomic relationship between African and Arabian Peninsula dromedary camels. Principle Component Analysis (PCA) and average genome-wide admixture analysis were be conducted on these data to tackle the objectives of these studies. Both of the two analyses conducted revealed phylogeographic distinction between these two camel populations. However, no breed-wise genetic classification has been revealed among the African (Sudanese) camel breeds. The Arabian Peninsula camel populations also show higher heterozygosity than the Sudanese camels. The results of this study explain the evolutionary history and migration of African dromedary camels from their center of domestication in the southern Arabian Peninsula. These outputs help scientists to further understand the evolutionary history of dromedary camels, which might impact in conserving the favorable genetic of this species.

Keywords: dromedary, genotyping-by-sequencing, Arabian Peninsula, Sudan

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989 Technology Transfer of Indigenous Technologies: Emerging Aid to Indian Health Sector

Authors: Tripta Dixit, Smita Sahu, William Selvamurthy, Sadhana Srivastava

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India is battling with the issues of accessibility, affordability and availability of quality health to the masses. Indian medical heritage which dated back to 3000 BC unveils the rich knowledge pool which has undergone a perceptible change over years, such as eradication of many communicable diseases, increasing individual awareness of quality health and import driven medical device market etc. Despite a slew of initiatives the holistic slogan of ‘health for all’ remains elusive and a concern for the nation. The 21st-century projects a myriad of challenges like cultural diversity, large population, demographic dividend and geographical segmentation leading to varied needs of people as per their regional conditions of climate, disease prevalence, nutrition and sanitation. But these challenges are also opportunities for the development of indigenous, low cost and accessible technologies to tackle them. This requires reinforcing the potential of indigenous technologies in coordination with prevailing health issues in various regions of country. This paper emphasis on the strategy for exploring the indigenous technologies with entrusted up-scaling to meet the diverse needs of the people. This review proposes to adopt technology transfer as a strategy to establish a vibrant ecosystem for identifying and up-scaling the indigenous medical technologies with diligent hand-holding for public health.

Keywords: health, indigenous, medical technology, technology transfer

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988 A QoS Aware Cluster Based Routing Algorithm for Wireless Mesh Network Using LZW Lossless Compression

Authors: J. S. Saini, P. P. K. Sandhu

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The multi-hop nature of Wireless Mesh Networks and the hasty progression of throughput demands results in multi- channels and multi-radios structures in mesh networks, but the main problem of co-channels interference reduces the total throughput, specifically in multi-hop networks. Quality of Service mentions a vast collection of networking technologies and techniques that guarantee the ability of a network to make available desired services with predictable results. Quality of Service (QoS) can be directed at a network interface, towards a specific server or router's performance, or in specific applications. Due to interference among various transmissions, the QoS routing in multi-hop wireless networks is formidable task. In case of multi-channel wireless network, since two transmissions using the same channel may interfere with each other. This paper has considered the Destination Sequenced Distance Vector (DSDV) routing protocol to locate the secure and optimised path. The proposed technique also utilizes the Lempel–Ziv–Welch (LZW) based lossless data compression and intra cluster data aggregation to enhance the communication between the source and the destination. The use of clustering has the ability to aggregate the multiple packets and locates a single route using the clusters to improve the intra cluster data aggregation. The use of the LZW based lossless data compression has ability to reduce the data packet size and hence it will consume less energy, thus increasing the network QoS. The MATLAB tool has been used to evaluate the effectiveness of the projected technique. The comparative analysis has shown that the proposed technique outperforms over the existing techniques.

Keywords: WMNS, QOS, flooding, collision avoidance, LZW, congestion control

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987 The Balance between the Two Characters of the Night: A Study on the Nightscape of Pei Ho Street and Yen Chow Street West in Sham Shui Po

Authors: Lei Danyang, Lu Jialiang

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As nightlife is getting richer in urban area, urban nightscape has become an increasingly important part of the urban landscape. Understanding urban nightscape from the perspec­tive of pedestrian perception is very important to improve the livability and walkability of a city. The purpose of this study is to analyze the nightscapes of two different urban forms. The research methods are literature investigation and field investigation. From analyzing the lighting, sensory ex­perience, and night activities, this research studies the two streets, Pei Ho Street and Yen Chow Street West in Sham Shui Po. Results revealed that the two streets are on the two extremes of the two characters of the night and a better balance needs to be found between them. Because of the different land usage and stakeholders, the two streets should play different roles in the nightscape, so their balance points are also different. On the one hand, Pei Ho Street, which has a strong commercial atmos­phere, should not only retain its vitality and diversity but also ensure its function of relaxation at night; on the other hand, in Yen Chow Street West, it is necessary to develop its potential of reconnecting people with the darkness of the night while ensur­ing its safety. These findings may not only provide policymak­ers with information to help them improve the nightscape and livability of the Sham Shui Po area but also help bridge the gap between research and design. In the future, more attention should be paid to pedestrian preference and nightscape perception of vulnerable groups.

Keywords: Hong Kong, pedestrian perception, Sham Shui Po, urban form, urban nightscape

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986 Early Gastric Cancer Prediction from Diet and Epidemiological Data Using Machine Learning in Mizoram Population

Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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985 Ethnolinguistic Identity and Language Policies: Negotiating Identity and Diversity in Modern Linguistic Environment in Malawi

Authors: Peter Mayeso Jiyajiya

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The question of language and identity in the post-colonial Africa has resulted in the policy inconsistencies and perceived wayward practices regarding language use. The need to reside and situate oneself in the global village has alienated local identities, with most countries, Malawi in particular promoting exogenous colonial language(s) at the expense of local languages that mirror people’s identities. This has brought a mismatch between language policy and implementation. The resultant effect has been alienation of the ‘Self’ from one’s indigenous identity and creation of the ‘other’ in the foreign identity, and the undermining of the linguistic rights of the minority language speakers. The need to negotiate the identity and modernity in the global village is thus imperative. The paper attempts to review the language situation in Malawi in light of the growing desire for international integration vis-à-vis the cultivation and maintenance of national ethnolinguistic identity. It further highlights the dilemma that the promotion of vernacular languages is facing in the modern Malawi. It also examines the Malawi language policy and its implementation. The failures, challenges, and inconsistencies are discussed in order to negotiate the position of minority languages in the modern Malawi. The paper notes that identity construction and maintenance within the framework of language policy in Malawi is undermined by attitudinal factors towards one’s culture and language. The paper then provides suggestions of negotiating identity in Malawi within the framework of globalisation through the placement of premiums on the minority languages.

Keywords: identity, language policy, minority languages, vernacular language

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984 Microsatellite-Based Genetic Variations and Relationships among Some Farmed Nile Tilapia Populations in Ghana: Implications for Nile Tilapia Culture

Authors: Acheampong Addo, Emmanuel Odartei Armah, Seth Koranteng Agyakwah, Ruby Asmah, Emmanuel Tetteh-Doku Mensah, Rhoda Lims Diyie, Sena Amewu, Catherine Ragasa, Edward Kofi Abban, Mike Yaw Osei-Atweneboana

Abstract:

The study investigated genetic variation and relationships among populations of Nile tilapia cultured in small-scale fish farms in selected regions of Ghana. A total of 700 samples were collected. All samples were screened with five microsatellite markers and results were analyzed using (Genetic Analysis in Excel), (Molecular and Evolutionary Genetic Analysis software, and Genpop on the web for Heterozygosity and Shannon diversity, (Analysis of Molecular Variance), and (Principal Coordinate Analysis). Fish from the 16 populations (made up of 14 farms and 2 selectively bred populations) clustered into three groups: 7 populations clustered with the GIFT-derived strain, 4 populations clustered with the Akosombo strain, and three populations were in a separate cluster. The clustering pattern indicated groups of different strains of Nile tilapia cultured. Mantel correlation test also showed low genetic variations among the 16 populations hence the need to boost seed quality in order to accelerate aquaculture production in Ghana.

Keywords: microsatellites, small- scale, Nile tilapia, akosombo strain, GIFT strain

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983 Occupational Health Assessment in a Telco Account: A Workplace Integrated Safety and Health and Cornell Musculoskeletal Discomfort Questionnaire Analysis Among Diverse Employees at Alorica

Authors: Karl Bryant Buan, Owaida Macadadaya Jr., Mon Eleazar Nonato, Zeke Andrew Palabrica, Charistabelle Mae Santiago

Abstract:

This study explored the occupational health risks faced by employees in the Business Process Outsourcing (BPO) industry, particularly in the Telco Account department of Alorica. The study used a stratified sampling method and a diagnostic tool called Workplace Integrated Safety and Health (WISH) Assessment to measure and evaluate the employees' perception of workplace health and safety. The results showed that more than 50% of call center workers reported feeling emotionally drained, sleep deprived, burnt out, and in need of anxiety or stress medication due to their work. Additionally, there was a significant difference in the perception of employee diversity, specifically in terms of leadership commitment, participation, policies, programs, and practices. The Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) results revealed that most employees complained of discomfort in their lower back, shoulder, upper back, neck, and hip. The researchers recommended an implementation plan for alternative work set-up, a satisfaction survey for employees, team-building activities or programs, and motivational approaches through benefits, incentives, and rewards.

Keywords: WISH assessment, CMDQ, ANOVA, diverse SOGIESC

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982 Identification of Microbial Community in an Anaerobic Reactor Treating Brewery Wastewater

Authors: Abimbola M. Enitan, John O. Odiyo, Feroz M. Swalaha

Abstract:

The study of microbial ecology and their function in anaerobic digestion processes are essential to control the biological processes. This is to know the symbiotic relationship between the microorganisms that are involved in the conversion of complex organic matter in the industrial wastewater to simple molecules. In this study, diversity and quantity of bacterial community in the granular sludge taken from the different compartments of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated using polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR). The phylogenetic analysis showed three major eubacteria phyla that belong to Proteobacteria, Firmicutes and Chloroflexi in the full-scale UASB reactor, with different groups populating different compartment. The result of qPCR assay showed high amount of eubacteria with increase in concentration along the reactor’s compartment. This study extends our understanding on the diverse, topological distribution and shifts in concentration of microbial communities in the different compartments of a full-scale UASB reactor treating brewery wastewater. The colonization and the trophic interactions among these microbial populations in reducing and transforming complex organic matter within the UASB reactors were established.

Keywords: bacteria, brewery wastewater, real-time quantitative PCR, UASB reactor

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981 The Developments Trend of Islamic Inscriptions in the Building Portals of Dezfoul City

Authors: Mahnoush Mahmoudi, Ali Chaeedeh

Abstract:

In the architecture of Iranian traditional houses, the ornamentations available in the inscriptions of houses entrance portal express the identity of architects and personality of houses owners and are rooted in their religious and national beliefs and faiths. The main hypothesis of this research is changing the physique and application of religious contents in compliance with the thoughts and beliefs of people in Dezfoul historical city in the epigraphs of houses entrance portals. The objective of this study is reviewing the development trend of texts, concepts and physique of inscriptions as well as analyzing the factors effective on the quality and diversity of application of inscriptions. The present research is an applied study and descriptive-analytical method has been applied, and the data was collected by library and survey studies. The population of this research includes historical houses, houses damaged in war (Iran & Iraq) and renovated and new tissue and new-built houses of Dezfoul, from Qajar era so far. Random sampling method has been applied in this study and dispersal area includes the city. Data analysis method in this study is qualitative and quantitative. The results of this study indicate that today the inscriptions available in the entrance portal of houses in Dezfoul comparing to inscriptions in Qajar1 and Pahlavi2 era is very simple and has lower aesthetic value. One of the causes for such superficial and contextual gap between inscriptions seems to be the war and renovations during and after destruction.

Keywords: architecture, islamic architecture, reconstruction, epigraph, inscription, entrance portal, Dezfoul

Procedia PDF Downloads 235
980 Affordable Aerodynamic Balance for Instrumentation in a Wind Tunnel Using Arduino

Authors: Pedro Ferreira, Alexandre Frugoli, Pedro Frugoli, Lucio Leonardo, Thais Cavalheri

Abstract:

The teaching of fluid mechanics in engineering courses is, in general, a source of great difficulties for learning. The possibility of the use of experiments with didactic wind tunnels can facilitate the education of future professionals. The objective of this proposal is the development of a low-cost aerodynamic balance to be used in a didactic wind tunnel. The set is comprised of an Arduino microcontroller, programmed by an open source software, linked to load cells built by students from another project. The didactic wind tunnel is 5,0m long and the test area is 90,0 cm x 90,0 cm x 150,0 cm. The Weq® electric motor, model W-22 of 9,2 HP, moves a fan with nine blades, each blade 32,0 cm long. The Weq® frequency inverter, model WEGCFW 08 (Vector Inverter) is responsible for wind speed control and also for the motor inversion of the rotational direction. A flat-convex profile prototype of airfoil was tested by measuring the drag and lift forces for certain attack angles; the air flux conditions remained constant, monitored by a Pitot tube connected to a EXTECH® Instruments digital pressure differential manometer Model HD755. The results indicate a good agreement with the theory. The choice of all of the components of this proposal resulted in a low-cost product providing a high level of specific knowledge of mechanics of fluids, which may be a good alternative to teaching in countries with scarce educational resources. The system also allows the expansion to measure other parameters like fluid velocity, temperature, pressure as well as the possibility of automation of other functions.

Keywords: aerodynamic balance, wind tunnel, strain gauge, load cell, Arduino, low-cost education

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979 Numerical Studies for Standard Bi-Conjugate Gradient Stabilized Method and the Parallel Variants for Solving Linear Equations

Authors: Kuniyoshi Abe

Abstract:

Bi-conjugate gradient (Bi-CG) is a well-known method for solving linear equations Ax = b, for x, where A is a given n-by-n matrix, and b is a given n-vector. Typically, the dimension of the linear equation is high and the matrix is sparse. A number of hybrid Bi-CG methods such as conjugate gradient squared (CGS), Bi-CG stabilized (Bi-CGSTAB), BiCGStab2, and BiCGstab(l) have been developed to improve the convergence of Bi-CG. Bi-CGSTAB has been most often used for efficiently solving the linear equation, but we have seen the convergence behavior with a long stagnation phase. In such cases, it is important to have Bi-CG coefficients that are as accurate as possible, and the stabilization strategy, which stabilizes the computation of the Bi-CG coefficients, has been proposed. It may avoid stagnation and lead to faster computation. Motivated by a large number of processors in present petascale high-performance computing hardware, the scalability of Krylov subspace methods on parallel computers has recently become increasingly prominent. The main bottleneck for efficient parallelization is the inner products which require a global reduction. The resulting global synchronization phases cause communication overhead on parallel computers. The parallel variants of Krylov subspace methods reducing the number of global communication phases and hiding the communication latency have been proposed. However, the numerical stability, specifically, the convergence speed of the parallel variants of Bi-CGSTAB may become worse than that of the standard Bi-CGSTAB. In this paper, therefore, we compare the convergence speed between the standard Bi-CGSTAB and the parallel variants by numerical experiments and show that the convergence speed of the standard Bi-CGSTAB is faster than the parallel variants. Moreover, we propose the stabilization strategy for the parallel variants.

Keywords: bi-conjugate gradient stabilized method, convergence speed, Krylov subspace methods, linear equations, parallel variant

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978 Antifungal Susceptibility of Yeasts Isolated from Clinical Samples from a Tertiary Hospital from State of Puebla

Authors: Ricardo Munguia-Perez, Nayeli Remigio-Alvarado, M.Miriam Hernandez-Arroyo, Elsa Castañeda-Roldan

Abstract:

Fungi have emerged as important pathogens causing morbidity and mortality mainly in immunosuppressed, malnourished and elderly patients. It has detected an increase in resistance to azoles primarily to fluconazol. The fungal infections have become a problem of public health for the resistance to antifungal agents, they have developed new antifungals with broad-spectrum. The aim of this study was determine the antifungal susceptibility of yeasts isolated from clinical samples (respiratory secretions, exudates, wounds, blood cultures, urine cultures) obtained from inpatients and outpatients of a tertiary hospital from State of Puebla. The antifungal susceptibility of the yeast from several clinical samples were determined by the CLS M44-A disk diffusion methods. 149 samples of yeast were analyzed. All species were 100% susceptible to nystatin and amphotericin B. Candida albicans showed resistance of 95.5 % to fluconazole, 50.7 % to 5-flurocytosine and 55.2 % intermediate susceptibility to ketoconazole. Candida glabrata 81.3 % was susceptibility to ketoconazole and 75 % to fluconazole, for the case of 5-flurocytosine the 56.3 % was susceptible. Candida krusei 100 % was susceptible to ketoconazole, 50 % to fluconazole and 37.5 % to 5-flurocytosine. The internal medicine have greater diversity of yeast, the samples have susceptibility of 64.7% to ketoconazole, 47.1 % to fluconazole and 27.5 % to 5-flurocytosine. Hospitalized patients are more resistant to fluconazole and nystatin, but in the case of outpatients presents resistance to ketoconazole.

Keywords: antifungal, susceptibility, yeast, clinical samples

Procedia PDF Downloads 318
977 Multivariate Data Analysis for Automatic Atrial Fibrillation Detection

Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

Abstract:

Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

Procedia PDF Downloads 252