Search results for: sequence data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25116

Search results for: sequence data

24816 The First Transcriptome Assembly of Marama Bean: An African Orphan Crop

Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

Abstract:

Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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24815 Synchronization of Bus Frames during Universal Serial Bus Transfer

Authors: Petr Šimek

Abstract:

This work deals with the problem of synchronization of bus frames during transmission using USB (Universal Serial Bus). The principles for synchronization between USB and the non-deterministic CAN (Controller Area Network) bus will be described here. Furthermore, the work deals with ensuring the time sequence of communication frames when receiving from multiple communication bus channels. The structure of a general object for storing frames from different types of communication buses, such as CAN and LIN (Local Interconnect Network), will be described here. Finally, an evaluation of the communication throughput of bus frames for USB High speed will be performed. The creation of this architecture was based on the analysis of the communication of control units with a large number of communication buses. For the design of the architecture, a test HW with a USB-HS interface was used, which received previously known messages, which were compared with the received result. The result of this investigation is the block architecture of the control program for test HW ensuring correct data transmission via the USB bus.

Keywords: analysis, CAN, interface, LIN, synchronization, USB

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24814 Evaluation of the Physico-Chemical and Microbial Properties of the Compost Leachate (CL) to Assess Its Role in the Bioremediation of Polyaromatic Hydrocarbons (PAHs)

Authors: Omaima A. Sharaf, Tarek A. Moussa, Said M. Badr El-Din, H. Moawad

Abstract:

Background: Polycyclic aromatic hydrocarbons (PAHs) pose great environmental and human health concerns for their widespread occurrence, persistence, and carcinogenic properties. PAHs releases due to anthropogenic activities to the wider environment have led to higher concentrations of these contaminants than would be expected from natural processes alone. This may result in a wide range of environmental problems that can accumulate in agricultural ecosystems, which threatened to become a negative impact on sustainable agricultural development. Thus, this study aimed to evaluate the physico-chemical, and microbial properties of the compost leachate (CL) to assess its role as nutrient and microbial source (biostimulation/bioaugmentation) for developing a cost-effective bioremediation technology for PAHs contaminated sites. Material and Methods: PAHs-degrading bacteria were isolated from CL that was collected from a composting site located in central Scotland, UK. Isolation was carried out by enrichment using phenanthrene (PHR), pyrene (PYR) and benzo(a)pyrene (BaP) as the sole source of carbon and energy. The isolates were characterized using a variety of phenotypic and molecular properties. Six different isolates were identified based on the difference in morphological and biochemical tests. The efficiency of these isolates in PAHs utilization was assessed. Further analysis was performed to define taxonomical status and phylogenic relation between the most potent PAHs-utilizing bacterial strains and other standard strains, using molecular approach by partial 16S rDNA gene sequence analysis. Results indicated that the 16S rDNA sequence analysis confirmed the results of biochemical identification, as both of biochemical and molecular identification of the isolates assigned them to Bacillus licheniformis, Pseudomonas aeruginosa, Alcaligenes faecalis, Serratia marcescens, Enterobacter cloacae and Providenicia which were identified as the prominent PAHs-utilizers isolated from CL. Conclusion: This study indicates that the CL samples contain a diverse population of PAHs-degrading bacteria and the use of CL may have a potential for bioremediation of PAHs contaminated sites.

Keywords: polycyclic aromatic hydrocarbons, physico-chemical analyses, compost leachate, microbial and biochemical analyses, phylogenic relations, 16S rDNA sequence analysis

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24813 Sequence Analysis and Molecular Cloning of PROTEOLYSIS 6 in Tomato

Authors: Nurulhikma Md Isa, Intan Elya Suka, Nur Farhana Roslan, Chew Bee Lynn

Abstract:

The evolutionarily conserved N-end rule pathway marks proteins for degradation by the Ubiquitin Proteosome System (UPS) based on the nature of their N-terminal residue. Proteins with a destabilizing N-terminal residue undergo a series of condition-dependent N-terminal modifications, resulting in their ubiquitination and degradation. Intensive research has been carried out in Arabidopsis previously. The group VII Ethylene Response Factor (ERFs) transcription factors are the first N-end rule pathway substrates found in Arabidopsis and their role in regulating oxygen sensing. ERFs also function as central hubs for the perception of gaseous signals in plants and control different plant developmental including germination, stomatal aperture, hypocotyl elongation and stress responses. However, nothing is known about the role of this pathway during fruit development and ripening aspect. The plant model system Arabidopsis cannot represent fleshy fruit model system therefore tomato is the best model plant to study. PROTEOLYSIS6 (PRT6) is an E3 ubiquitin ligase of the N-end rule pathway. Two homologs of PRT6 sequences have been identified in tomato genome database using the PRT6 protein sequence from model plant Arabidopsis thaliana. Homology search against Ensemble Plant database (tomato) showed Solyc09g010830.2 is the best hit with highest score of 1143, e-value of 0.0 and 61.3% identity compare to the second hit Solyc10g084760.1. Further homology search was done using NCBI Blast database to validate the data. The result showed best gene hit was XP_010325853.1 of uncharacterized protein LOC101255129 (Solanum lycopersicum) with highest score of 1601, e-value 0.0 and 48% identity. Both Solyc09g010830.2 and uncharacterized protein LOC101255129 were genes located at chromosome 9. Further validation was carried out using BLASTP program between these two sequences (Solyc09g010830.2 and uncharacterized protein LOC101255129) to investigate whether they were the same proteins represent PRT6 in tomato. Results showed that both proteins have 100 % identity, indicates that they were the same gene represents PRT6 in tomato. In addition, we used two different RNAi constructs that were driven under 35S and Polygalacturonase (PG) promoters to study the function of PRT6 during tomato developmental stages and ripening processes.

Keywords: ERFs, PRT6, tomato, ubiquitin

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24812 A Comprehensive Analysis of the Phylogenetic Signal in Ramp Sequences in 211 Vertebrates

Authors: Lauren M. McKinnon, Justin B. Miller, Michael F. Whiting, John S. K. Kauwe, Perry G. Ridge

Abstract:

Background: Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Methods: Ramp sequences were compared from 211 vertebrates (110 Mammalian and 101 non-mammalian). The presence and absence of ramp sequences were analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life taxonomy to determine the number of parallelisms and reversals that occurred, and these results were compared to what would be expected due to random chance. Lastly, aligned nucleotides in ramp sequences were compared to the rest of the sequence in order to examine possible differences in phylogenetic signal between these regions of the gene. Results: Parsimony and maximum likelihood analyses of the presence/absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, the retention index of ramp sequences is significantly higher than would be expected due to random chance (p-value = 0). A chi-square analysis of completely orthologous ramp sequences resulted in a p-value of approximately zero as compared to random chance. Discussion: Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches.

Keywords: codon usage bias, phylogenetics, phylogenomics, ramp sequence

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24811 Antibody Reactivity of Synthetic Peptides Belonging to Proteins Encoded by Genes Located in Mycobacterium tuberculosis-Specific Genomic Regions of Differences

Authors: Abu Salim Mustafa

Abstract:

The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nob-tuberculous mycobacteria. The three identified M. tuberculosis-specific immunodominant peptides may be useful in the serological diagnosis of tuberculosis.

Keywords: genomic regions of differences, Mycobacterium tuberculossis, peptides, serodiagnosis

Procedia PDF Downloads 165
24810 Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

Abstract:

Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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24809 Embedded Digital Image System

Authors: Dawei Li, Cheng Liu, Yiteng Liu

Abstract:

This paper introduces an embedded digital image system for Chinese space environment vertical exploration sounding rocket. In order to record the flight status of the sounding rocket as well as the payloads, an onboard embedded image processing system based on ADV212, a JPEG2000 compression chip, is designed in this paper. Since the sounding rocket is not designed to be recovered, all image data should be transmitted to the ground station before the re-entry while the downlink band used for the image transmission is only about 600 kbps. Under the same condition of compression ratio compared with other algorithm, JPEG2000 standard algorithm can achieve better image quality. So JPEG2000 image compression is applied under this condition with a limited downlink data band. This embedded image system supports lossless to 200:1 real time compression, with two cameras to monitor nose ejection and motor separation, and two cameras to monitor boom deployment. The encoder, ADV7182, receives PAL signal from the camera, then output the ITU-R BT.656 signal to ADV212. ADV7182 switches between four input video channels as the program sequence. Two SRAMs are used for Ping-pong operation and one 512 Mb SDRAM for buffering high frame-rate images. The whole image system has the characteristics of low power dissipation, low cost, small size and high reliability, which is rather suitable for this sounding rocket application.

Keywords: ADV212, image system, JPEG2000, sounding rocket

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24808 Robust and Transparent Spread Spectrum Audio Watermarking

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter

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24807 Orbital Tuning of Marl-Limestone Alternations (Upper Tithonian to Upper Berriasian) in North-South Axis (Tunisia): Geochronology and Sequence Implications

Authors: Hamdi Omar Omar, Hela Fakhfakh, Chokri Yaich

Abstract:

This work reflects the integration of different techniques, such as field sampling and observations, magnetic susceptibility measurement, cyclostratigaraphy and sequence stratigraphy. The combination of these results allows us to reconstruct the environmental evolution of the Sidi Khalif Formation in the North-South Axis (NOSA), aged of Upper Tithonian, Berriasian and Lower Valanginian. Six sedimentary facies were identified and are primarily influenced by open marine sedimentation receiving increasing terrigenous influx. Spectral analysis, based on MS variation (for the outcropped section) and wireline logging gamma ray (GR) variation (for the sub-area section) show a pervasive dominance of 405-kyr eccentricity cycles with the expression of 100-kyr eccentricity, obliquity and precession. This study provides (for the first time) a precise duration of 2.4 myr for the outcropped Sidi Khalif Formation with a sedimentation rate of 5.4 cm/kyr and the sub-area section to 3.24 myr with a sedimentation rate of 7.64 cm/kyr. We outlined 27 5th-order depositional sequences, 8 Milankovitch depositional sequences and 2 major 3rd-order cycles for the outcropping section, controlled by the long eccentricity (405 kyr) cycles and the precession index cycles. This study has demonstrated the potential of MS and GR to be used as proxies to develop an astronomically calibrated time-scale for the Mesozoic era.

Keywords: Berriasian, magnetic susceptibility, orbital tuning, Sidi Khalif Formation

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24806 Implementation of an IoT Sensor Data Collection and Analysis Library

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

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24805 Estimation and Forecasting with a Quantile AR Model for Financial Returns

Authors: Yuzhi Cai

Abstract:

This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

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24804 Government (Big) Data Ecosystem: Definition, Classification of Actors, and Their Roles

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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24803 Valorization of Waste Reverse Osmosis Desalination Brine and Crystallization Sequence Approach for Kainite Recovery

Authors: Ayoub Bouazza, Ali Faddouli, Said Amal, Rachid Benhida, Khaoula Khaless

Abstract:

Brine waste generated from reverse osmosis (RO) desalination plants contains various valuable compounds, mainly salts, trace elements, and organic matter. These wastes are up to two times saltier than standard seawater. Therefore, there is a strong economic interest in recovering these salts. The current practice in desalination plants is to reject the brine back to the sea, which affects the marine ecosystem and the environment. Our study aims to bring forth a reliable management solution for the valorisation of waste brines. Natural evaporation, isothermal evaporation at 25°C and 50°C, and evaporation using continuous heating were used to crystallize valuable salts from a reverse osmosis desalination plant brine located on the Moroccan Atlantic coast. The crystallization sequence of the brine was studied in comparison with standard seawater. The X-Ray Diffraction (XRD) of the precipitated solid phases showed similar results, where halite was the main solid phase precipitated from both the brine and seawater. However, Jänecke diagram prediction, along with FREZCHEM simulations, showed that Kainite should crystallize before Epsomite and Carnallite. As the absence of kainite formation in many experiments in the literature has been related to the metastability of kainite and the critical relative humidity conditions, and the precipitation of K–Mg salts is very sensitive to climatic conditions. An evaporation process is proposed as a solution to achieve the predicted crystallization path and to affirm the recovery of Kainite.

Keywords: salts crystallization, reverse osmosis, solar evaporation, frezchem, ZLD

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24802 Government Big Data Ecosystem: A Systematic Literature Review

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

Procedia PDF Downloads 204
24801 A Machine Learning Decision Support Framework for Industrial Engineering Purposes

Authors: Anli Du Preez, James Bekker

Abstract:

Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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24800 Development of Microsatellite Markers for Genetic Variation Analysis in House Cricket, Acheta domesticus

Authors: Yash M. Gupta, Kittisak Buddhachat, Surin Peyachoknagul, Somjit Homchan

Abstract:

The house cricket, Acheta domesticus is one of the commonly found species of field crickets. Although it is very commonly used as food and feed, the genomic information of house cricket is still missing for genetic investigation. DNA sequencing technology has evolved over the decades, and it has also revolutionized the molecular marker development for genetic analysis. In the present study, we have sequenced the whole genome of A. domesticus using illumina platform based HiSeq X Ten sequencing technology for searching simple sequence repeats (SSRs) in DNA to develop polymorphic microsatellite markers for population genetic analysis. A total of 112,157 SSRs with primer pairs were identified, 91 randomly selected SSRs used to check DNA amplification, of which nine primers were polymorphic. These microsatellite markers have shown cross-amplification with other three species of crickets which are Gryllus bimaculatus, Gryllus testaceus and Brachytrupes portentosus. These nine polymorphic microsatellite markers were used to check genetic variation for forty-five individuals of A. domesticus, Phitsanulok population, Thailand. For nine loci, the number of alleles was ranging from 5 to 15. The observed heterozygosity was ranged from 0.4091 to 0.7556. These microsatellite markers will facilitate population genetic analysis for future studies of A. domesticus populations. Moreover, the transferability of these SSR makers would also enable researchers to conduct genetic studies for other closely related species.

Keywords: cross-amplification, microsatellite markers, observed heterozygosity, population genetic, simple sequence repeats

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24799 Providing Security to Private Cloud Using Advanced Encryption Standard Algorithm

Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

Abstract:

In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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24798 Pale, Firm and Non-Exudative (PFN): An Emerging Major Broiler Breast Meat Group

Authors: Cintia Midori Kaminishikawahara, Fernanda Jéssica Mendonça, Moisés Grespan, Elza Iouko Ida, Massami Shimokomaki, Adriana Lourenço Soares

Abstract:

The quality of broiler breast meat is changing as a result of continuing emphasis on genetically bird’s selection for efficiently higher meat production. The consumer is experiencing a cooked product that is drier and less juicy when consumed. Breast meat has been classified as PSE (pale, soft, exudative), DFD (dark, firm, dry) and normal color meat. However, recently variations of this color have been observed and they are not in line with the specificity of the meat functional properties. Thus, the objective of this work was to report the finding of a new pale meat color group characterized as Pale, Firm and Non-exudative (PFN) based on its pH, color, meat functional properties and micro structural evaluation. Breast meat fillets samples (n=1045) from commercial line were classified into PSE (pH ≤5.8, L* ≥ 53.0), PFN (pH > 5.8 and L* ≥ 53.0) and Normal (pH >5.8 and L* < 53.0), based on pH and L* values. In sequence, a total of 30 samples of each group were analyzed for the water holding capacity (WHC) and shear force (SF). The incidence was 9.1% for PSE meat, 85.7% for PFN and 5.2% for Normal meat. The PSE meat presented lower values of WHC (P ≤ 0.05) followed in sequence by PFN and Normal samples and also the SF values of fresh PFN was higher than PSE meat (P ≤ 0.05) and similar to Normal samples. Under optical microscopy, the cell diameter was 10% higher for PFN in relation to PSE meat and similar to Normal meat. These preliminary results indicate an emerging group of breast meat and it should be considered that the Pale, Firm and Non-exudative should be considered as an ideal broiler breast meat quality.

Keywords: broiler PSE meat, light microscopy, texture, water holding capacity

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24797 Strain Based Failure Criterion for Composite Notched Laminates

Authors: Ibrahim A. Elsayed, Mohamed H. Elalfy, Mostafa M. Abdalla

Abstract:

A strain-based failure criterion for composite notched laminates is introduced where the most critical stress concentration factor for the anisotropic notched laminates could be related to the failure of the corresponding quasi-isotropic laminate and the anisotropy ratio of the laminate. The proposed criterion will simplify the design of composites to meet notched failure requirements by eliminating the need for the detailed specifications of the stacking sequence at the preliminary design stage. The designer will be able to design based on the stiffness of the laminate, then at a later stage, select an appropriate stacking sequence to meet the stiffness requirements. The failure strains for the notched laminates are computed using the material’s Omni-strain envelope. The concept of Omni-strain envelope concerns the region of average strain where the laminate is safe regardless of ply orientation. In this work, we use Hashin’s failure criteria and the strains around the hole are computed using Savin’s analytic solution. A progressive damage analysis study has been conducted where the failure loads for the notched laminates are computed using finite element analysis. The failure strains are computed and used to estimate the concentration factor. It is found that the correlation found using Savin’s analytic solution predicts the same ratio of concentration factors between anisotropic and quasi-isotropic laminates as the more expensive progressive failure analysis.

Keywords: anisotropy ratio, failure criteria, notched laminates, Omni-strain envelope, savin’s solution

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24796 A Study on the Treatment of Municipal Waste Water Using Sequencing Batch Reactor

Authors: Bhaven N. Tandel, Athira Rajeev

Abstract:

Sequencing batch reactor process is a suspended growth process operating under non-steady state conditions which utilizes a fill and draw reactor with complete mixing during the batch reaction step (after filling) and where the subsequent steps of aeration and clarification occur in the same tank. All sequencing batch reactor systems have five steps in common, which are carried out in sequence as follows, (1) fill (2) react (3) settle (sedimentation/clarification) (4) draw (decant) and (5) idle. The study was carried out in a sequencing batch reactor of dimensions 44cmx30cmx70cm with a working volume of 40 L. Mechanical stirrer of 100 rpm was used to provide continuous mixing in the react period and oxygen was supplied by fish tank aerators. The duration of a complete cycle of sequencing batch reactor was 8 hours. The cycle period was divided into different phases in sequence as follows-0.25 hours fill phase, 6 hours react period, 1 hour settling phase, 0.5 hours decant period and 0.25 hours idle phase. The study consisted of two runs, run 1 and run 2. Run 1 consisted of 6 hours aerobic react period and run 2 consisted of 3 hours aerobic react period followed by 3 hours anoxic react period. The influent wastewater used for the study had COD, BOD, NH3-N and TKN concentrations of 308.03±48.94 mg/L, 100.36±22.05 mg/L, 14.12±1.18 mg/L, and 24.72±2.21 mg/L respectively. Run 1 had an average COD removal efficiency of 41.28%, BOD removal efficiency of 56.25%, NH3-N removal efficiency of 86.19% and TKN removal efficiency of 54.4%. Run 2 had an average COD removal efficiency of 63.19%, BOD removal efficiency of 73.85%, NH3-N removal efficiency of 90.74% and TKN removal efficiency of 65.25%. It was observed that run 2 gave better performance than run 1 in the removal of COD, BOD and TKN.

Keywords: municipal waste water, aerobic, anoxic, sequencing batch reactor

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24795 Business Intelligence for Profiling of Telecommunication Customer

Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

Abstract:

Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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24794 Gas While Drilling (GWD) Classification in Betara Complex; An Effective Approachment to Optimize Future Candidate of Gumai Reservoir

Authors: I. Gusti Agung Aditya Surya Wibawa, Andri Syafriya, Beiruny Syam

Abstract:

Gumai Formation which acts as regional seal for Talang Akar Formation becomes one of the most prolific reservoir in South Sumatra Basin and the primary exploration target in this area. Marine conditions were eventually established during the continuation of transgression sequence leads an open marine facies deposition in Early Miocene. Marine clastic deposits where calcareous shales, claystone and siltstones interbedded with fine-grained calcareous and glauconitic sandstones are the domination of lithology which targeted as the hydrocarbon reservoir. All this time, the main objective of PetroChina’s exploration and production in Betara area is only from Lower Talang Akar Formation. Successful testing in some exploration wells which flowed gas & condensate from Gumai Formation, opened the opportunity to optimize new reservoir objective in Betara area. Limitation of conventional wireline logs data in Gumai interval is generating technical challenge in term of geological approach. A utilization of Gas While Drilling indicator initiated with the objective to determine the next Gumai reservoir candidate which capable to increase Jabung hydrocarbon discoveries. This paper describes how Gas While Drilling indicator is processed to generate potential and non-potential zone by cut-off analysis. Validation which performed by correlation and comparison with well logs, Drill Stem Test (DST), and Reservoir Performance Monitor (RPM) data succeed to observe Gumai reservoir in Betara Complex. After we integrated all of data, we are able to generate a Betara Complex potential map and overlaid with reservoir characterization distribution as a part of risk assessment in term of potential zone presence. Mud log utilization and geophysical data information successfully covered the geological challenges in this study.

Keywords: Gumai, gas while drilling, classification, reservoir, potential

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24793 In silico and in vitro Investigation of the Role of Acinetobacter baumannii in the Pathogenesis of Multiple Sclerosis

Authors: Kieren Luellman, Makenzi Rockwell, Eduardo Callegari, Nichole Haag, Chun Wu

Abstract:

Multiple sclerosis (MS) is an autoimmune disorder that damages the myelin sheath of neurons in the central nervous system. The presence of Acinetobacter bacteria and anti-Acinetobacter antibodies in MS patients has led to the hypothesis that the bacteria may contribute to MS pathogenesis. In this study, the protein sequences of Acinetobacter baumannii were compared to five peptides from three mammalian myelin proteins, i.e., Proteolipid Protein (PLP): PLP 139-151, PLP 178-191, Myelin Basic Protein (MBP): MBP 84-104 and Myelin Oligodendrocyte Glycoprotein (MOG): MOG 35-55 and MOG 92-106 respectively, known to induce experimental autoimmune encephalomyelitis (EAE), a condition similar to MS. We found 11 hits (i.e., with five or more amino acid sequence similarity) in Acinetobacter baumannii, which are identical or similar to PLP139-151, 32 hits to PLP178-191, 35 to MBP 84-104, 41 hits to MOG 35-55 and 26 hits to MOG92-106. In addition, Western blotting was used to assess possible interaction between the bacterial proteins and human anti-MBP, anti-MOG, and anti-PLP antibodies produced in rabbits, corresponding to MBP 84-104, MOG 35-55, and PLP 139-151, respectively. We found that both human Polyclonal anti-MOG antibody and anti-PLP antibody recognized a protein or more proteins of the same molecular mass of around 25 kDa. in Acinetobacter baumannii. The results suggested that this/these protein(s) might potentially serve as antigen(s) to induce anti-MOG antibody and anti-PLP antibody production in mammalian B cells. The proteomic study identified 433 hits, among which the sequence of Acinetobacter baumannii protein 491 subunit A matches a previously published enzyme Acinetobacter 3-Oxoadipate CoA-Transferase, in which a fragment of its peptide was observed to recognize MS patient serum via ELISA method. Our findings might pave the road to understanding one of the pathogenesis mechanisms of MS.

Keywords: multiple sclerosis, pathogenesis, Acinetobacter baumannii, antibody recognition

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24792 Palynology of the Cretaceous Deposits of the Southeast Sirt Basin, Libya

Authors: Khaled Mahmud Gaddah

Abstract:

Cretaceous deposits in the southeast of the Sirt Basin of Libya occur in several grabens that formed during a major phase of rifting related to the opening of the Tethys. They include continental deposits of Early Cretaceous age that belong to the Nubian Formation and marginal to fully marine deposits of Late Cretaceous age that belong to the Lidam Formation and transitional beds. The sequence was extensively sampled from twenty-two boreholes and palynologically analysed. Much of the sequence is barren. However, subordinate shales in all formations yield diverse assemblages of poorly to well preserved and thermally middle to post mature palynomorphs. Most of the assemblages contain non-marine palynomorphs (spores, pollen, and freshwater algae), although some contain rare marine elements (dinoflagellate cysts and acritarchs). The palynofloras enabled the recognition of six assemblage zones of the late Barremian-Turonian age based on the dominant and base/top occurrences of stratigraphically useful palynomorphs: AI (Afropollisspp.-Aequitriraditesspinulosus) of late Barremian age; AIIa (Scenedesmusbifidus-S. sp.) of late Barremian?-early Aptian age; AIIb (Afropollisoperculatus-A. zonatus) of Aptian age; AIII (Crybelosporitespannuceus-Afropollisjardinus) of early Albian age; AIV (Subtilisphaera sp.-Lophosphaeridiumspp.) of Cenomanian-?Turonian age; AIV (Pediastrumbifidites-Leiosphaeridiaspp.) of Cenomanian?-Turonian age. These assemblages are comparable to others from Northern Gondwana (particularly from Libya and Egypt) and correspond to established Cretaceous palynofloral provinces. Palynofacies analysis is used to interpret the depositional environments, and five palynofacies types are recognised that reflect increasing marine influence up section.

Keywords: palynology, palynomorphs, palynofacies, tethys, sirt basin

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24791 Imputation Technique for Feature Selection in Microarray Data Set

Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam

Abstract:

Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics

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24790 PDDA: Priority-Based, Dynamic Data Aggregation Approach for Sensor-Based Big Data Framework

Authors: Lutful Karim, Mohammed S. Al-kahtani

Abstract:

Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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24789 De Novo Assembly and Characterization of the Transcriptome from the Fluoroacetate Producing Plant, Dichapetalum Cymosum

Authors: Selisha A. Sooklal, Phelelani Mpangase, Shaun Aron, Karl Rumbold

Abstract:

Organically bound fluorine (C-F bond) is extremely rare in nature. Despite this, the first fluorinated secondary metabolite, fluoroacetate, was isolated from the plant Dichapetalum cymosum (commonly known as Gifblaar). However, the enzyme responsible for fluorination (fluorinase) in Gifblaar was never isolated and very little progress has been achieved in understanding this process in higher plants. Fluorinated compounds have vast applications in the pharmaceutical, agrochemical and fine chemicals industries. Consequently, an enzyme capable of catalysing a C-F bond has great potential as a biocatalyst in the industry considering that the field of fluorination is virtually synthetic. As with any biocatalyst, a range of these enzymes are required. Therefore, it is imperative to expand the exploration for novel fluorinases. This study aimed to gain molecular insights into secondary metabolite biosynthesis in Gifblaar using a high-throughput sequencing-based approach. Mechanical wounding studies were performed using Gifblaar leaf tissue in order to induce expression of the fluorinase. The transcriptome of the wounded and unwounded plant was then sequenced on the Illumina HiSeq platform. A total of 26.4 million short sequence reads were assembled into 77 845 transcripts using Trinity. Overall, 68.6 % of transcripts were annotated with gene identities using public databases (SwissProt, TrEMBL, GO, COG, Pfam, EC) with an E-value threshold of 1E-05. Sequences exhibited the greatest homology to the model plant, Arabidopsis thaliana (27 %). A total of 244 annotated transcripts were found to be differentially expressed between the wounded and unwounded plant. In addition, secondary metabolic pathways present in Gifblaar were successfully reconstructed using Pathway tools. Due to lack of genetic information for plant fluorinases, a transcript failed to be annotated as a fluorinating enzyme. Thus, a local database containing the 5 existing bacterial fluorinases was created. Fifteen transcripts having homology to partial regions of existing fluorinases were found. In efforts to obtain the full coding sequence of the Gifblaar fluorinase, primers were designed targeting the regions of homology and genome walking will be performed to amplify the unknown regions. This is the first genetic data available for Gifblaar. It has provided novel insights into the mechanisms of metabolite biosynthesis and will allow for the discovery of the first eukaryotic fluorinase.

Keywords: biocatalyst, fluorinase, gifblaar, transcriptome

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24788 Symmetric Key Encryption Algorithm Using Indian Traditional Musical Scale for Information Security

Authors: Aishwarya Talapuru, Sri Silpa Padmanabhuni, B. Jyoshna

Abstract:

Cryptography helps in preventing threats to information security by providing various algorithms. This study introduces a new symmetric key encryption algorithm for information security which is linked with the "raagas" which means Indian traditional scale and pattern of music notes. This algorithm takes the plain text as input and starts its encryption process. The algorithm then randomly selects a raaga from the list of raagas that is assumed to be present with both sender and the receiver. The plain text is associated with the thus selected raaga and an intermediate cipher-text is formed as the algorithm converts the plain text characters into other characters, depending upon the rules of the algorithm. This intermediate code or cipher text is arranged in various patterns in three different rounds of encryption performed. The total number of rounds in the algorithm is equal to the multiples of 3. To be more specific, the outcome or output of the sequence of first three rounds is again passed as the input to this sequence of rounds recursively, till the total number of rounds of encryption is performed. The raaga selected by the algorithm and the number of rounds performed will be specified at an arbitrary location in the key, in addition to important information regarding the rounds of encryption, embedded in the key which is known by the sender and interpreted only by the receiver, thereby making the algorithm hack proof. The key can be constructed of any number of bits without any restriction to the size. A software application is also developed to demonstrate this process of encryption, which dynamically takes the plain text as input and readily generates the cipher text as output. Therefore, this algorithm stands as one of the strongest tools for information security.

Keywords: cipher text, cryptography, plaintext, raaga

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24787 Elastic Collisions of Electrons with DNA and Water From 10 eV to 100 KeV: Scar Macro Investigation

Authors: Aouina Nabila Yasmina, Zine El Abidine Chaoui

Abstract:

Recently, understanding the interactions of electrons with the DNA molecule and its components has attracted considerable interest because DNA is the main site damaged by ionizing radiation. The interactions of radiation with DNA induce a variety of molecular damage such as single-strand breaks, double-strand breaks, basic damage, cross-links between proteins and DNA, and others, or the formation of free radicals, which, by chemical reactions with DNA, can also lead to breakage of the strand. One factor that can contribute significantly to these processes is the effect of water hydration on the formation and reaction of radiation induced by these radicals in and / or around DNA. B-DNA requires about 30% by weight of water to maintain its native conformation in the crystalline state. The transformation depends on various factors such as sequence, ion composition, concentration and water activity. Partial dehydration converts it to DNA-A. The present study shows the results of theoretical calculations for positrons and electrons elastic scattering with DNA medium and water over a broad energy range from 10 eV to 100 keV. Indeed, electron elastic cross sections and elastic mean free paths are calculated using a corrected form of the independent atom method, taking into account the geometry of the biomolecule (SCAR macro). Moreover, the elastic scattering of electrons and positrons by atoms of the biomolecule was evaluated by means of relativistic (Dirac) partial wave analysis. Our calculated results are compared with theoretical data available in the literature in the absence of experimental data, in particular for positron. As a central result, our electron elastic cross sections are in good agreement with existing theoretical data in the range of 10 eV to 1 keV.

Keywords: elastic cross scrion, elastic mean free path, scar macro method, electron collision

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