Search results for: temporal sequences
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1682

Search results for: temporal sequences

1352 Urban Landscape Composition and Configuration Dynamics and Expansion of Hawassa City Analysis, Ethiopia Using Satellite Images and Spatial Metrics Approach

Authors: Berhanu Keno Terfa

Abstract:

To understand the consequences of urbanization, accurate, and long-term representation of urban dynamics is essential. Remote sensing data from various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used. An integrated method, landscape metrics, built-up density, and urban growth type analysis were employed to analyze the pattern, process, and overall growth status in the city. The result showed that the built-up area had increased by 541.3% between 1987 and 2017, at an average annual increment of 8.9%. The area of urban expansion in a city has tripled during the 2005-2017 period as compared to 187- 1995. The major growth took place in the east and southeast directions during 1987–1995 period, whereas predominant built-up development was observed in south and southeast direction during 1995–2017 period. The analysis using landscape metrics and urban typologies showed that Hawassa experienced a fragmented and irregular spatiotemporal urban growth patterns, mostly by extension, suggesting a strong tendency towards sprawl in the past three decades.

Keywords: Hawassa, spatial patterns, remote sensing, multi-temporal, urban sprawl

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1351 Variation of Phytoplankton Biomass in the East China Sea Based on MODIS Data

Authors: Yumei Wu, Xiaoyan Dang, Shenglong Yang, Shengmao Zhang

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The East China Sea is one of four main seas in China, where there are many fishery resources. Some important fishing grounds, such as Zhousan fishing ground important to society. But the eco-environment is destroyed seriously due to the rapid developing of industry and economy these years. In this paper, about twenty-year satellite data from MODIS and the statistical information of marine environment from the China marine environmental quality bulletin were applied to do the research. The chlorophyll-a concentration data from MODIS were dealt with in the East China Sea and then used to analyze the features and variations of plankton biomass in recent years. The statistics method was used to obtain their spatial and temporal features. The plankton biomass in the Yangtze River estuary and the Taizhou region were highest. The high phytoplankton biomass usually appeared between the 88th day to the 240th day (end-March - August). In the peak time of phytoplankton blooms, the Taizhou islands was the earliest, and the South China Sea was the latest. The intensity and period of phytoplankton blooms were connected with the global climate change. This work give us confidence to use satellite data to do more researches about the China Sea, and it also provides some help for us to know about the eco-environmental variation of the East China Sea and regional effect from global climate change.

Keywords: the East China Sea, phytoplankton biomass, temporal and spatial variation, phytoplankton bloom

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1350 An Examination of Changes on Natural Vegetation due to Charcoal Production Using Multi Temporal Land SAT Data

Authors: T. Garba, Y. Y. Babanyara, M. Isah, A. K. Muktari, R. Y. Abdullahi

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The increased in demand of fuel wood for heating, cooking and sometimes bakery has continued to exert appreciable impact on natural vegetation. This study focus on the use of multi-temporal data from land sat TM of 1986, land sat EMT of 1999 and lands sat ETM of 2006 to investigate the changes of Natural Vegetation resulting from charcoal production activities. The three images were classified based on bare soil, built up areas, cultivated land, and natural vegetation, Rock out crop and water bodies. From the classified images Land sat TM of 1986 it shows natural vegetation of the study area to be 308,941.48 hectares equivalent to 50% of the area it then reduces to 278,061.21 which is 42.92% in 1999 it again depreciated to 199,647.81 in 2006 equivalent to 30.83% of the area. Consequently cultivated continue increasing from 259,346.80 hectares (42%) in 1986 to 312,966.27 hectares (48.3%) in 1999 and then to 341.719.92 hectares (52.78%). These show that within the span of 20 years (1986 to 2006) the natural vegetation is depreciated by 119,293.81 hectares. This implies that if the menace is not control the natural might likely be lost in another twenty years. This is because forest cleared for charcoal production is normally converted to farmland. The study therefore concluded that there is the need for alternatives source of domestic energy such as the use of biomass which can easily be accessible and affordable to people. In addition, the study recommended that there should be strong policies enforcement for the protection forest reserved.

Keywords: charcoal, classification, data, images, land use, natural vegetation

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1349 Mitigating Ruminal Methanogenesis Through Genomic and Transcriptomic Approaches

Authors: Muhammad Adeel Arshad, Faiz-Ul Hassan, Yanfen Cheng

Abstract:

According to FAO, enteric methane (CH4) production is about 44% of all greenhouse gas emissions from the livestock sector. Ruminants produce CH4 as a result of fermentation of feed in the rumen especially from roughages which yield more CH4 per unit of biomass ingested as compared to concentrates. Efficient ruminal fermentation is not possible without abating CO2 and CH4. Methane abatement strategies are required to curb the predicted rise in emissions associated with greater ruminant production in future to meet ever increasing animal protein requirements. Ecology of ruminal methanogenesis and avenues for its mitigation can be identified through various genomic and transcriptomic techniques. Programs such as Hungate1000 and the Global Rumen Census have been launched to enhance our understanding about global ruminal microbial communities. Through Hungate1000 project, a comprehensive reference set of rumen microbial genome sequences has been developed from cultivated rumen bacteria and methanogenic archaea along with representative rumen anaerobic fungi and ciliate protozoa cultures. But still many species of rumen microbes are underrepresented especially uncultivable microbes. Lack of sequence information specific to the rumen's microbial community has inhibited efforts to use genomic data to identify specific set of species and their target genes involved in methanogenesis. Metagenomic and metatranscriptomic study of entire microbial rumen populations offer new perspectives to understand interaction of methanogens with other rumen microbes and their potential association with total gas and methane production. Deep understanding of methanogenic pathway will help to devise potentially effective strategies to abate methane production while increasing feed efficiency in ruminants.

Keywords: Genome sequences, Hungate1000, methanogens, ruminal fermentation

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1348 Integrating Time-Series and High-Spatial Remote Sensing Data Based on Multilevel Decision Fusion

Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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1347 Author Profiling: Prediction of Learners’ Gender on a MOOC Platform Based on Learners’ Comments

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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1346 A Framework for Security Risk Level Measures Using CVSS for Vulnerability Categories

Authors: Umesh Kumar Singh, Chanchala Joshi

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With increasing dependency on IT infrastructure, the main objective of a system administrator is to maintain a stable and secure network, with ensuring that the network is robust enough against malicious network users like attackers and intruders. Security risk management provides a way to manage the growing threats to infrastructures or system. This paper proposes a framework for risk level estimation which uses vulnerability database National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) and the Common Vulnerability Scoring System (CVSS). The proposed framework measures the frequency of vulnerability exploitation; converges this measured frequency with standard CVSS score and estimates the security risk level which helps in automated and reasonable security management. In this paper equation for the Temporal score calculation with respect to availability of remediation plan is derived and further, frequency of exploitation is calculated with determined temporal score. The frequency of exploitation along with CVSS score is used to calculate the security risk level of the system. The proposed framework uses the CVSS vectors for risk level estimation and measures the security level of specific network environment, which assists system administrator for assessment of security risks and making decision related to mitigation of security risks.

Keywords: CVSS score, risk level, security measurement, vulnerability category

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1345 The Meaning in Life and the Content of Mental Images of Temporal Mental Simulations in Poles and Americans

Authors: Katarzyna Pasternak

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Experiencing the meaning of life is widely recognised as a vital element of well-being and central human motivation. Studies have shown that a higher meaning of life is associated, among other things, with a higher quality of life, higher levels of happiness and better declared health. The subject of the study is the meaning in life measured with The Meaning in Life Questionnaire and the presence of such emotions as nostalgia, awe and hope, and the content of imaginations measured after temporal mental simulations in Americans and Poles. The respondents had to imagine themselves in future, in 40 years and describe two events that would take place at that time. Next, participants assessed the importance of the events described by them, recognised whether during their journey through time they felt awe, hope and nostalgia, and answered the questionnaire examining the meaning in life. 204 (102 from Poland 102 from the USA ) people aged 21 to 60 participated in the study. The study checked whether there were differences in the content of the imaginations of the respondents from Poland and USA, and whether there were statistically significant difference between the declared sense of meaning in life among participants from both countries. The result of the study hane shown that there were no differences in the overall result obtained by the participants in The Meaning in Life Questionnaire , while there were statistically significant differences among the subscales of the questionnaire. It turned out that Americans have a higher presence of meaning in life than Poles, but they obtained lower results in searching of meaning in life. Studies have also shown that there was a statistically significant difference between Poles and Americans in feeling awe after a mental simulation. Poles felt higher level of awe. Images about the future differed between Poles and Americans. Poles judged that the events they described were very important to them. Interestingly, the content of American participants’ imaginations was dominated by topics related to the future of the world, ecology and world peace. There were also ideas about nice moments spent with friends and family. Among Poles, ideas related to professional career and development as well as family events dominated. Research shows that despite the lack of differences in the general meaning in life, Poles are more focused on searching for meaning in life than Americans. The study shows interesting differences between the two cultures.

Keywords: meaning in life, mental simulations, imaginations, temporal mental simulations, future, cultural differences

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1344 Characterization of Fateh Sagar Wetland and Its Catchment Area at Udaipur City, (Raj.) India, Using High Resolution Data

Authors: Parul Bhalla, Sarvesh Palria

Abstract:

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

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1343 Carbon Based Classification of Aquaporin Proteins: A New Proposal

Authors: Parul Johri, Mala Trivedi

Abstract:

Major Intrinsic proteins (MIPs), actively involved in the passive transport of small polar molecules across the membranes of almost all living organisms. MIPs that specifically transport water molecules are named aquaporins (AQPs). The permeability of membranes is actively controlled by the regulation of the amount of different MIPs present but also in some cases by phosphorylation and dephosphorylation of the channel. Based on sequence similarity, MIPs have been classified into many categories. All of the proteins are made up of the 20 amino acids, the only difference is there in their orientations. Again all the 20 amino acids are made up of the basic five elements namely: carbon, hydrogen, oxygen, sulphur and nitrogen. These elements are responsible for giving the amino acids the properties of hydrophilicity/hydrophobicity which play an important role in protein interactions. The hydrophobic amino acids characteristically have greater number of carbon atoms as carbon is the main element which contributes to hydrophobic interactions in proteins. It is observed that the carbon level of proteins in different species is different. In the present work, we have taken a sample set of 150 aquaporins proteins from Uniprot database and a dynamic programming code was written to calculate the carbon percentage for each sequence. This carbon percentage was further used to barcode the aqauporins of animals and plants. The protein taken from Oryza sativa, Zea mays and Arabidopsis thaliana preferred to have carbon percentage of 31.8 to 35, whereas on the other hand sequences taken from Mus musculus, Saccharomyces cerevisiae, Homo sapiens, Bos Taurus, and Rattus norvegicus preferred to have carbon percentage of 31 to 33.7. This clearly demarks the carbon range in the aquaporin proteins from plant and animal origin. Hence the atom level analysis of protein sequences can provide us with better results as compared to the residue level comparison.

Keywords: aquaporins, carbon, dynamic prgramming, MIPs

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1342 Molecular Epidemiology of Circulating Adenovirus Types in Acute Conjunctivitis Cases in Chandigarh, North India

Authors: Mini P. Singh, Jagat Ram, Archit Kumar, Tripti Rungta, Jasmine Khurana, Amit Gupta, R. K. Ratho

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Introduction: Human adenovirus is the most common agent involved in viral conjunctivitis. The clinical manifestations vary with different serotypes. The identification of the circulating strains followed by phylogenetic analysis can be helpful in understanding the origin and transmission of the disease. The present study aimed to carry out molecular epidemiology of the adenovirus types in the patients with conjunctivitis presenting to the eye centre of a tertiary care hospital in North India. Materials and Methods: The conjunctival swabs were collected from 23 suspected adenoviral conjunctivitis patients between April-August, 2014 and transported in viral transport media. The samples were subjected to nested PCR targeting hexon gene of human adenovirus. The band size of 956bp was eluted and 8 representative positive samples were subjected to sequencing. The sequences were analyzed by using CLUSTALX2.1 and MEGA 5.1 software. Results: The male: female ratio was found to be 3.6:1. The mean age of presenting patients was 43.95 years (+17.2). Approximately 52.1% (12/23) of patients presented with bilateral involvement while 47.8% (11/23) with unilateral involvement of the eye. Human adenovirus DNA could be detected in 65.2% (15/23) of the patients. The phylogenetic analysis revealed presence of serotype 8 in 7 patients and serotype 4 in one patient. The serotype 8 sequences showed 99-100% identity with Tunisian, Indian and Japanese strains. The adenovirus serotype 4 strains had 100% identity with strains from Tunisia, China and USA. Conclusion: Human adenovirus was found be an important etiological agent for conjunctivitis in our set up. The phylogenetic analysis showed that the predominant circulating strains in our epidemic keratoconjunctivitis were serotypes 8 and 4.

Keywords: conjunctivitis, human adenovirus, molecular epidemiology, phylogenetics

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1341 Toward Particular Series with (k,h)-Jacobsthal Sequence

Authors: Seyyd Hossein Jafari-Petroudi, Maryam Pirouz

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This note is devoted to (k; h)-Jacobsthal sequence as a general term of particular series. More formulas for nth term and sum of the first n terms of series that their general terms are (k; h)-Jacobsthal sequence and (k; h)-Jacobsthal-Petroudi sequence are derived. Finally other properties of these sequences are represented.

Keywords: (k, h)-Jacobsthal sequence, (k, h)-Jacobsthal Petroudisequence, recursive relation, sum

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1340 Application of GIS Techniques for Analysing Urban Built-Up Growth of Class-I Indian Cities: A Case Study of Surat

Authors: Purba Biswas, Priyanka Dey

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Worldwide rapid urbanisation has accelerated city expansion in both developed and developing nations. This unprecedented urbanisation trend due to the increasing population and economic growth has caused challenges for the decision-makers in city planning and urban management. Metropolitan cities, class-I towns, and major urban centres undergo a continuous process of evolution due to interaction between socio-cultural and economic attributes. This constant evolution leads to urban expansion in all directions. Understanding the patterns and dynamics of urban built-up growth is crucial for policymakers, urban planners, and researchers, as it aids in resource management, decision-making, and the development of sustainable strategies to address the complexities associated with rapid urbanisation. Identifying spatio-temporal patterns of urban growth has emerged as a crucial challenge in monitoring and assessing present and future trends in urban development. Analysing urban growth patterns and tracking changes in land use is an important aspect of urban studies. This study analyses spatio-temporal urban transformations and land-use and land cover changes using remote sensing and GIS techniques. Built-up growth analysis has been done for the city of Surat as a case example, using the GIS tools of NDBI and GIS models of the Built-up Urban Density Index and Shannon Entropy Index to identify trends and the geographical direction of transformation from 2005 to 2020. Surat is one of the fastest-growing urban centres in both the state and the nation, ranking as the 4th fastest-growing city globally. This study analyses the dynamics of urban built-up area transformations both zone-wise and geographical direction-wise, in which their trend, rate, and magnitude were calculated for the period of 15 years. This study also highlights the need for analysing and monitoring the urban growth pattern of class-I cities in India using spatio-temporal and quantitative techniques like GIS for improved urban management.

Keywords: urban expansion, built-up, geographic information system, remote sensing, Shannon’s entropy

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1339 Dynamics Pattern of Land Use and Land Cover Change and Its Driving Factors Based on a Cellular Automata Markov Model: A Case Study at Ibb Governorate, Yemen

Authors: Abdulkarem Qasem Dammag, Basema Qasim Dammag, Jian Dai

Abstract:

Change in Land use and Land cover (LU/LC) has a profound impact on the area's natural, economic, and ecological development, and the search for drivers of land cover change is one of the fundamental issues of LU/LC change. The study aimed to assess the temporal and Spatio-temporal dynamics of LU/LC in the past and to predict the future using Landsat images by exploring the characteristics of different LU/LC types. Spatio-temporal patterns of LU/LC change in Ibb Governorate, Yemen, were analyzed based on RS and GIS from 1990, 2005, and 2020. A socioeconomic survey and key informant interviews were used to assess potential drivers of LU/LC. The results showed that from 1990 to 2020, the total area of vegetation land decreased by 5.3%, while the area of barren land, grassland, built-up area, and waterbody increased by 2.7%, 1.6%, 1.04%, and 0.06%, respectively. Based on socio-economic surveys and key informant interviews, natural factors had a significant and long-term impact on land change. In contrast, site construction and socio-economic factors were the main driving forces affecting land change in a short time scale. The analysis results have been linked to the CA-Markov Land Use simulation and forecasting model for the years 2035 and 2050. The simulation results revealed from the period 2020 to 2050, the trend of dynamic changes in land use, where the total area of barren land decreased by 7.0% and grassland by 0.2%, while the vegetation land, built-up area, and waterbody increased by 4.6%, 2.6%, and 0.1 %, respectively. Overall, these findings provide LULC's past and future trends and identify drivers, which can play an important role in sustainable land use planning and management by balancing and coordinating urban growth and land use and can also be used at the regional level in different levels to provide as a reference. In addition, the results provide scientific guidance to government departments and local decision-makers in future land-use planning through dynamic monitoring of LU/LC change.

Keywords: LU/LC change, CA-Markov model, driving forces, change detection, LU/LC change simulation

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1338 Metagenomics-Based Molecular Epidemiology of Viral Diseases

Authors: Vyacheslav Furtak, Merja Roivainen, Olga Mirochnichenko, Majid Laassri, Bella Bidzhieva, Tatiana Zagorodnyaya, Vladimir Chizhikov, Konstantin Chumakov

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Molecular epidemiology and environmental surveillance are parts of a rational strategy to control infectious diseases. They have been widely used in the worldwide campaign to eradicate poliomyelitis, which otherwise would be complicated by the inability to rapidly respond to outbreaks and determine sources of the infection. The conventional scheme involves isolation of viruses from patients and the environment, followed by their identification by nucleotide sequences analysis to determine phylogenetic relationships. This is a tedious and time-consuming process that yields definitive results when it may be too late to implement countermeasures. Because of the difficulty of high-throughput full-genome sequencing, most such studies are conducted by sequencing only capsid genes or their parts. Therefore the important information about the contribution of other parts of the genome and inter- and intra-species recombination to viral evolution is not captured. Here we propose a new approach based on the rapid concentration of sewage samples with tangential flow filtration followed by deep sequencing and reconstruction of nucleotide sequences of viruses present in the samples. The entire nucleic acids content of each sample is sequenced, thus preserving in digital format the complete spectrum of viruses. A set of rapid algorithms was developed to separate deep sequence reads into discrete populations corresponding to each virus and assemble them into full-length consensus contigs, as well as to generate a complete profile of sequence heterogeneities in each of them. This provides an effective approach to study molecular epidemiology and evolution of natural viral populations.

Keywords: poliovirus, eradication, environmental surveillance, laboratory diagnosis

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1337 Regression-Based Approach for Development of a Cuff-Less Non-Intrusive Cardiovascular Health Monitor

Authors: Pranav Gulati, Isha Sharma

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Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

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1336 Contribution of Remote Sensing and GIS to the Study of the Impact of the Salinity of Sebkhas on the Quality of Groundwater: Case of Sebkhet Halk El Menjel (Sousse)

Authors: Gannouni Sonia, Hammami Asma, Saidi Salwa, Rebai Noamen

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Water resources in Tunisia have experienced quantitative and qualitative degradation, especially when talking about wetlands and Sbekhas. Indeed, the objective of this work is to study the spatio-temporal evolution of salinity for 29 years (from 1987 to 2016). A study of the connection between surface water and groundwater is necessary to know the degree of influence of the Sebkha brines on the water table. The evolution of surface salinity is determined by remote sensing based on Landsat TM and OLI/TIRS satellite images of the years 1987, 2007, 2010, and 2016. The processing of these images allowed us to determine the NDVI(Normalized Difference Vegetation Index), the salinity index, and the surface temperature around Sebkha. In addition, through a geographic information system(GIS), we could establish a map of the distribution of salinity in the subsurface of the water table of Chott Mariem and Hergla/SidiBouAli/Kondar. The results of image processing and the calculation of the index and surface temperature show an increase in salinity downstream of in addition to the sebkha and the development of vegetation cover upstream and the western part of the sebkha. This richness may be due both to contamination by seawater infiltration from the barrier beach of Hergla as well as the passage of groundwater to the sebkha.

Keywords: spatio-temporal monitoring, salinity, satellite images, NDVI, sebkha

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1335 A Ground Observation Based Climatology of Winter Fog: Study over the Indo-Gangetic Plains, India

Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.

Keywords: fog, climatology, Mann-Kendall test, trend analysis, spatial variability, temporal variability, visibility

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1334 The New Insight about Interspecies Transmission of Iranian H9N2 Influenza Viruses from Avian to Human

Authors: Masoud Soltanialvar, Ali Bagherpour

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Documented cases of human infection with H9N2 avian influenza viruses, first detected in 1999 in Hong Kong and China, indicate that these viruses can be directly transmitted from birds to humans. In this study, we characterized the mutation in the Hemagglutinin (HA) genes and proteins that correlates with a shift in affinity of the Hemagglutinin (HA) protein from the “avian” type sialic receptors to the “human” type in 10 Iranian isolates. We delineated the genomes and receptor binding profile of HA gene of some field isolates and established their phylogenetic relationship to the other Asian H9N2 sub lineages. A total of 1200 tissue samples collected from 40 farms located in various states of Iran during 2008 – 2010 as part of a program to monitor Avian Influenza Viruses (AIV) infection. To determine the genetic relationship of Iranian viruses, the Hemagglutinin (HA) genes from ten isolates were amplified and sequenced (by RT-PCR method). Nucleotide sequences (orf) of the (HA) genes were used for phylogenetic tree construction. Deduced amino acid sequences showed the presence of L226 (234 in H9 numbering) in all ten Iranian isolates which indicates a preference to binding of α (2–6) sialic acid receptors, so these Iranian H9N2 viruses have the potential to infect human beings. These isolates showed high degree of homology with 2 human H9N2 isolates A/HK/1073/99, A/HK/1074/99. Phylogenetic analysis of showed that all the HA genes of the Iranian H9N2 viruses fall into a single group within a G1-like sublineage which had contributed as donor of six internal genes to H5N1 highly pathogenic avian influenza. The results of this study indicated that all Iranian viruses have the potential to emerge as highly pathogenic influenza virus, and considering the homology of these isolates with human H9N2 strains, it seems that the potential of these avian influenza isolates to infect human should not be overlooked.

Keywords: influenza virus, hemagglutinin, neuraminidase, Iran

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1333 Multilocus Phylogenetic Approach Reveals Informative DNA Barcodes for Studying Evolution and Taxonomy of Fusarium Fungi

Authors: Alexander A. Stakheev, Larisa V. Samokhvalova, Sergey K. Zavriev

Abstract:

Fusarium fungi are among the most devastating plant pathogens distributed all over the world. Significant reduction of grain yield and quality caused by Fusarium leads to multi-billion dollar annual losses to the world agricultural production. These organisms can also cause infections in immunocompromised persons and produce the wide range of mycotoxins, such as trichothecenes, fumonisins, and zearalenone, which are hazardous to human and animal health. Identification of Fusarium fungi based on the morphology of spores and spore-forming structures, colony color and appearance on specific culture media is often very complicated due to the high similarity of these features for closely related species. Modern Fusarium taxonomy increasingly uses data of crossing experiments (biological species concept) and genetic polymorphism analysis (phylogenetic species concept). A number of novel Fusarium sibling species has been established using DNA barcoding techniques. Species recognition is best made with the combined phylogeny of intron-rich protein coding genes and ribosomal DNA sequences. However, the internal transcribed spacer of (ITS), which is considered to be universal DNA barcode for Fungi, is not suitable for genus Fusarium, because of its insufficient variability between closely related species and the presence of non-orthologous copies in the genome. Nowadays, the translation elongation factor 1 alpha (TEF1α) gene is the “gold standard” of Fusarium taxonomy, but the search for novel informative markers is still needed. In this study, we used two novel DNA markers, frataxin (FXN) and heat shock protein 90 (HSP90) to discover phylogenetic relationships between Fusarium species. Multilocus phylogenetic analysis based on partial sequences of TEF1α, FXN, HSP90, as well as intergenic spacer of ribosomal DNA (IGS), beta-tubulin (β-TUB) and phosphate permease (PHO) genes has been conducted for 120 isolates of 19 Fusarium species from different climatic zones of Russia and neighboring countries using maximum likelihood (ML) and maximum parsimony (MP) algorithms. Our analyses revealed that FXN and HSP90 genes could be considered as informative phylogenetic markers, suitable for evolutionary and taxonomic studies of Fusarium genus. It has been shown that PHO gene possesses more variable (22 %) and parsimony informative (19 %) characters than other markers, including TEF1α (12 % and 9 %, correspondingly) when used for elucidating phylogenetic relationships between F. avenaceum and its closest relatives – F. tricinctum, F. acuminatum, F. torulosum. Application of novel DNA barcodes confirmed the fact that F. arthrosporioides do not represent a separate species but only a subspecies of F. avenaceum. Phylogeny based on partial PHO and FXN sequences revealed the presence of separate cluster of four F. avenaceum strains which were closer to F. torulosum than to major F. avenaceum clade. The strain F-846 from Moldova, morphologically identified as F. poae, formed a separate lineage in all the constructed dendrograms, and could potentially be considered as a separate species, but more information is needed to confirm this conclusion. Variable sites in PHO sequences were used for the first-time development of specific qPCR-based diagnostic assays for F. acuminatum and F. torulosum. This work was supported by Russian Foundation for Basic Research (grant № 15-29-02527).

Keywords: DNA barcode, fusarium, identification, phylogenetics, taxonomy

Procedia PDF Downloads 324
1332 Spatio-Temporal Pest Risk Analysis with ‘BioClass’

Authors: Vladimir A. Todiras

Abstract:

Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

Procedia PDF Downloads 282
1331 Aerosol Radiative Forcing Over Indian Subcontinent for 2000-2021 Using Satellite Observations

Authors: Shreya Srivastava, Sushovan Ghosh, Sagnik Dey

Abstract:

Aerosols directly affect Earth’s radiation budget by scattering and absorbing incoming solar radiation and outgoing terrestrial radiation. While the uncertainty in aerosol radiative forcing (ARF) has decreased over the years, it is still higher than that of greenhouse gas forcing, particularly in the South Asian region, due to high heterogeneity in their chemical properties. Understanding the Spatio-temporal heterogeneity of aerosol composition is critical in improving climate prediction. Studies using satellite data, in-situ and aircraft measurements, and models have investigated the Spatio-temporal variability of aerosol characteristics. In this study, we have taken aerosol data from Multi-angle Imaging Spectro-Radiometer (MISR) level-2 version 23 aerosol products retrieved at 4.4 km and radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 21 years (2000-2021) over the Indian subcontinent. MISR aerosol product includes size and shapes segregated aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). Additionally, 74 aerosol mixtures are included in version 23 data that is used for aerosol speciation. We have seasonally mapped aerosol optical and microphysical properties from MISR for India at quarter degrees resolution. Results show strong Spatio-temporal variability, with a constant higher value of AOD for the Indo-Gangetic Plain (IGP). The contribution of small-size particles is higher throughout the year, spatially during winter months. SSA is found to be overestimated where absorbing particles are present. The climatological map of short wave (SW) ARF at the top of the atmosphere (TOA) shows a strong cooling except in only a few places (values ranging from +2.5o to -22.5o). Cooling due to aerosols is higher in the absence of clouds. Higher negative values of ARF are found over the IGP region, given the high aerosol concentration above the region. Surface ARF values are everywhere negative for our study domain, with higher values in clear conditions. The results strongly correlate with AOD from MISR and ARF from CERES.

Keywords: aerosol Radiative forcing (ARF), aerosol composition, single scattering albedo (SSA), CERES

Procedia PDF Downloads 54
1330 Traffic Prediction with Raw Data Utilization and Context Building

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

Abstract:

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

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

Procedia PDF Downloads 129
1329 In-Depth Investigations on the Sequences of Accidents of Powered Two Wheelers Based on Police Crash Reports of Medan, North Sumatera Province Indonesia, Using Decision Aiding Processes

Authors: Bangun F., Crevits B., Bellet T., Banet A., Boy G. A., Katili I.

Abstract:

This paper seeks the incoherencies in cognitive process during an accident of Powered Two Wheelers (PTW) by understanding the factual sequences of events and causal relations for each case of accident. The principle of this approach is undertaking in-depth investigations on case per case of PTW accidents based on elaborate data acquisitions on accident sites that officially stamped in Police Crash Report (PCRs) 2012 of Medan with criteria, involved at least one PTW and resulted in serious injury and fatalities. The analysis takes into account four modules: accident chronologies, perpetrator, and victims, injury surveillance, vehicles and road infrastructures, comprising of traffic facilities, road geometry, road alignments and weather. The proposal for improvement could have provided a favorable influence on the chain of functional processes and events leading to collision. Decision Aiding Processes (DAP) assists in structuring different entities at different decisional levels, as each of these entities has its own objectives and constraints. The entities (A) are classified into 6 groups of accidents: solo PTW accidents; PTW vs. PTW; PTW vs. pedestrian; PTW vs. motor-trishaw; and PTW vs. other vehicles and consecutive crashes. The entities are also distinguished into 4 decisional levels: level of road users and street systems; operational level (crash-attended police officers or CAPO and road engineers), tactical level (Regional Traffic Police, Department of Transportation, and Department of Public Work), and strategic level (Traffic Police Headquarters (TCPHI)), parliament, Ministry of Transportation and Ministry of Public Work). These classifications will lead to conceptualization of Problem Situations (P) and Problem Formulations (I) in DAP context. The DAP concerns the sequences process of the incidents until the time the accident occurs, which can be modelled in terms of five activities of procedural rationality: identification on initial human features (IHF), investigation on proponents attributes (PrAT), on Injury Surveillance (IS), on the interaction between IHF and PrAt and IS (intercorrelation), then unravel the sequences of incidents; filtering and disclosure, which include: what needs to activate, modify or change or remove, what is new and what is priority. These can relate to the activation or modification or new establishment of law. The PrAt encompasses the problems of environmental, road infrastructure, road and traffic facilities, and road geometry. The evaluation model (MP) is generated to bridge P and I since MP is produced by the intercorrelations among IHF, PrAT and IS extracted from the PCRs 2012 of Medan. There are 7 findings of incoherences: lack of knowledge and awareness on the traffic regulations and the risks of accidents, especially when riding between 0 < x < 10 km from house, riding between 22 p.m.–05.30 a.m.; lack of engagements on procurement of IHF Data by CAPO; lack of competency of CAPO on data procurement in accident-sites; no intercorrelation among IHF and PrAt and IS in the database systems of PCRs; lack of maintenance and supervision on the availabilities and the capacities of traffic facilities and road infrastructure; instrumental bias with wash-back impacts towards the TCPHI; technical robustness with wash-back impacts towards the CAPO and TCPHI.

Keywords: decision aiding processes, evaluation model, PTW accidents, police crash reports

Procedia PDF Downloads 159
1328 The Magnetic Susceptibility of the Late Quaternary Loess in North-East of Iran and Its Correlation with Other Palaeoclimatical Parameters

Authors: Fereshteh M. Haskouei, Habib Alimohammadian

Abstract:

Magnetic susceptibility (χ) is operational to identify of late quaternary glacial-interglacial cycles in loess-paleosol sequences. It is well accepted that many loess-paleosol sequences bear witness to cold-dry/warm-humid periods, well known as glacial-interglacial cycles, respectively. For this study, loess-paleosol sequence of north-east of Iran was magnetically investigated. The study area is situated at about 8 km away of Neka city, on the main road of Sari-Behshahr, in Mazandaran Province, north of Iran. The youngest deposits of study area are the late Quaternary wind-blown accumulations. In this study, the total number of 117 samples was collected from loess-paleosols units. After that, the natural remnant magnetization (NRM) and magnetic susceptibility (MS) of the samples were measured. Variation of MS of more than 110 loess samples was plotted to reveal the correlation of the MS and paleoclimatic changes. This study aims reconstruction of climatic changes (glacial-interglacial and stadials-interstadials cycles). To confirm our results we compared MS (χ) and the curves of other investigations in paleoclimatology. This correspondence abled us to recognize worldly events in the study area such as: Younger Dryas, the Last Glacial Maximum (LGM), deglaciation of Northern Hemisphere etc. The obtained magnetic data indicate that during almost 50 ka, at least two glacial-interglacial periods occurred in north-east of Iran. Further, variation of χ values revealed short period of climatically cycles known as stadials-interstadials. We recognized 4 stadials and a single stadial as colder sub-periods for S0 (recently soil-paleosol) and S2 (lower paleosol), respectively, Moreover, we recognized 6 warmer sub-periods (interstadials) for L1 (upper loess) and one interstadial L2 (lower loess).

Keywords: glacial-interglacial cycles, Iran, last glacial maximum (LGM), loess, magnetic susceptibility (χ), Neka, stadials-interstadials sub-periods, younger dryas

Procedia PDF Downloads 124
1327 Signal Processing of the Blood Pressure and Characterization

Authors: Hadj Abd El Kader Benghenia, Fethi Bereksi Reguig

Abstract:

In clinical medicine, blood pressure, raised blood hemodynamic monitoring is rich pathophysiological information of cardiovascular system, of course described through factors such as: blood volume, arterial compliance and peripheral resistance. In this work, we are interested in analyzing these signals to propose a detection algorithm to delineate the different sequences and especially systolic blood pressure (SBP), diastolic blood pressure (DBP), and the wave and dicrotic to do their analysis in order to extract the cardiovascular parameters.

Keywords: blood pressure, SBP, DBP, detection algorithm

Procedia PDF Downloads 439
1326 Complete Genome Sequence Analysis of Pasteurella multocida Subspecies multocida Serotype A Strain PMTB2.1

Authors: Shagufta Jabeen, Faez J. Firdaus Abdullah, Zunita Zakaria, Nurulfiza M. Isa, Yung C. Tan, Wai Y. Yee, Abdul R. Omar

Abstract:

Pasteurella multocida (PM) is an important veterinary opportunistic pathogen particularly associated with septicemic pasteurellosis, pneumonic pasteurellosis and hemorrhagic septicemia in cattle and buffaloes. P. multocida serotype A has been reported to cause fatal pneumonia and septicemia. Pasteurella multocida subspecies multocida of serotype A Malaysian isolate PMTB2.1 was first isolated from buffaloes died of septicemia. In this study, the genome of P. multocida strain PMTB2.1 was sequenced using third-generation sequencing technology, PacBio RS2 system and analyzed bioinformatically via de novo analysis followed by in-depth analysis based on comparative genomics. Bioinformatics analysis based on de novo assembly of PacBio raw reads generated 3 contigs followed by gap filling of aligned contigs with PCR sequencing, generated a single contiguous circular chromosome with a genomic size of 2,315,138 bp and a GC content of approximately 40.32% (Accession number CP007205). The PMTB2.1 genome comprised of 2,176 protein-coding sequences, 6 rRNA operons and 56 tRNA and 4 ncRNAs sequences. The comparative genome sequence analysis of PMTB2.1 with nine complete genomes which include Actinobacillus pleuropneumoniae, Haemophilus parasuis, Escherichia coli and five P. multocida complete genome sequences including, PM70, PM36950, PMHN06, PM3480, PMHB01 and PMTB2.1 was carried out based on OrthoMCL analysis and Venn diagram. The analysis showed that 282 CDs (13%) are unique to PMTB2.1and 1,125 CDs with orthologs in all. This reflects overall close relationship of these bacteria and supports the classification in the Gamma subdivision of the Proteobacteria. In addition, genomic distance analysis among all nine genomes indicated that PMTB2.1 is closely related with other five Pasteurella species with genomic distance less than 0.13. Synteny analysis shows subtle differences in genetic structures among different P.multocida indicating the dynamics of frequent gene transfer events among different P. multocida strains. However, PM3480 and PM70 exhibited exceptionally large structural variation since they were swine and chicken isolates. Furthermore, genomic structure of PMTB2.1 is more resembling that of PM36950 with a genomic size difference of approximately 34,380 kb (smaller than PM36950) and strain-specific Integrative and Conjugative Elements (ICE) which was found only in PM36950 is absent in PMTB2.1. Meanwhile, two intact prophages sequences of approximately 62 kb were found to be present only in PMTB2.1. One of phage is similar to transposable phage SfMu. The phylogenomic tree was constructed and rooted with E. coli, A. pleuropneumoniae and H. parasuis based on OrthoMCL analysis. The genomes of P. multocida strain PMTB2.1 were clustered with bovine isolates of P. multocida strain PM36950 and PMHB01 and were separated from avian isolate PM70 and swine isolates PM3480 and PMHN06 and are distant from Actinobacillus and Haemophilus. Previous studies based on Single Nucleotide Polymorphism (SNPs) and Multilocus Sequence Typing (MLST) unable to show a clear phylogenetic relatedness between Pasteurella multocida and the different host. In conclusion, this study has provided insight on the genomic structure of PMTB2.1 in terms of potential genes that can function as virulence factors for future study in elucidating the mechanisms behind the ability of the bacteria in causing diseases in susceptible animals.

Keywords: comparative genomics, DNA sequencing, phage, phylogenomics

Procedia PDF Downloads 188
1325 Detection of MspI Polymorphism and SNP of GH Gene in Some Camel Breeds Reared in Egypt

Authors: Sekena H. Abd El-Aziem, Heba A. M. Abd El-Kader, Sally S. Alam, Othman E. Othman

Abstract:

Growth hormone (GH) is an anabolic hormone synthesized and secreted by the somatotroph cells of the anterior lobe of the pituitary gland in a circadian and pulsatile manner, the pattern of which plays an important role in postnatal longitudinal growth and development, tissue growth, lactation, reproduction as well as protein, lipid and carbohydrate metabolism. The aim of this study was to detect the genetic polymorphism of GH gene in five camel breeds reared in Egypt; Sudany, Somali, Mowaled, Maghrabi and Falahy, using PCR-RFLP technique. Also this work aimed to identify the single nucleotide polymorphism between different genotypes detected in these camel breeds. The amplified fragment of camel GH at 613-bp was digested with the restriction enzyme MspI and the result revealed the presence of three different genotypes; CC, CT and TT in tested breeds and significant differences were recorded in the genotype frequencies between these camel breeds. The result showed that the Maghrabi breed that is classified as a dual purpose camels had higher frequency for allele C (0.75) than those in the other tested four breeds. The sequence analysis declared the presence of a SNP (C→T) at position 264 in the amplified fragment which is responsible for the destruction of the restriction site C^CGG and consequently the appearance of two different alleles C and T. The nucleotide sequences of camel GH alleles T and C were submitted to nucleotide sequences database NCBI/Bankit/GenBank and have accession numbers: KP143517 and KP143518, respectively. It is concluded that only one SNP C→T was detected in GH gene among the five tested camel breeds reared in Egypt and this nucleotide substitution can be used as a marker for the genetic biodiversity between camel breeds reared in Egypt. Also, due to the possible association between allele C and higher growth rate, we can used it in MAS for camels and enter the camels possess this allele in breeding program as a way for enhancement of growth trait in camel breeds reared in Egypt.

Keywords: camel breeds in Egypt, GH, PCR-RFLP, SNPs

Procedia PDF Downloads 467
1324 Understanding Cognitive Fatigue From FMRI Scans With Self-supervised Learning

Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

Abstract:

Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

Procedia PDF Downloads 191
1323 Speech Enhancement Using Wavelet Coefficients Masking with Local Binary Patterns

Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

Abstract:

In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

Procedia PDF Downloads 230