Search results for: switching sequences
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1046

Search results for: switching sequences

716 Systematic Identification and Quantification of Substrate Specificity Determinants in Human Protein Kinases

Authors: Manuel A. Alonso-Tarajano, Roberto Mosca, Patrick Aloy

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Protein kinases participate in a myriad of cellular processes of major biomedical interest. The in vivo substrate specificity of these enzymes is a process determined by several factors, and despite several years of research on the topic, is still far from being totally understood. In the present work, we have quantified the contributions to the kinase substrate specificity of i) the phosphorylation sites and their surrounding residues in the sequence and of ii) the association of kinases to adaptor or scaffold proteins. We have used position-specific scoring matrices (PSSMs), to represent the stretches of sequences phosphorylated by 93 families of kinases. We have found negative correlations between the number of sequences from which a PSSM is generated and the statistical significance and the performance of that PSSM. Using a subset of 22 statistically significant PSSMs, we have identified specificity determinant residues (SDRs) for 86% of the corresponding kinase families. Our results suggest that different SDRs can function as positive or negative elements of substrate recognition by the different families of kinases. Additionally, we have found that human proteins with known function as adaptors or scaffolds (kAS) tend to interact with a significantly large fraction of the substrates of the kinases to which they associate. Based on this characteristic we have identified a set of 279 potential adaptors/scaffolds (pAS) for human kinases, which is enriched in Pfam domains and functional terms tightly related to the proposed function. Moreover, our results show that for 74.6% of the kinase– pAS association found, the pAS colocalize with the substrates of the kinases they are associated to. Finally, we have found evidence suggesting that the association of kinases to adaptors and scaffolds, may contribute significantly to diminish the in vivo substrate crossed- specificity of protein kinases. In general, our results indicate the relevance of several SDRs for both the positive and negative selection of phosphorylation sites by kinase families and also suggest that the association of kinases to pAS proteins may be an important factor for the localization of the enzymes with their set of substrates.

Keywords: kinase, phosphorylation, substrate specificity, adaptors, scaffolds, cellular colocalization

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715 Processing and Evaluation of Jute Fiber Reinforced Hybrid Composites

Authors: Mohammad W. Dewan, Jahangir Alam, Khurshida Sharmin

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Synthetic fibers (carbon, glass, aramid, etc.) are generally utilized to make composite materials for better mechanical and thermal properties. However, they are expensive and non-biodegradable. In the perspective of Bangladesh, jute fibers are available, inexpensive, and comprising good mechanical properties. The improved properties (i.e., low cost, low density, eco-friendly) of natural fibers have made them a promising reinforcement in hybrid composites without sacrificing mechanical properties. In this study, jute and e-glass fiber reinforced hybrid composite materials are fabricated utilizing hand lay-up followed by a compression molding technique. Room temperature cured two-part epoxy resin is used as a matrix. Approximate 6-7 mm thick composite panels are fabricated utilizing 17 layers of woven glass and jute fibers with different fiber layering sequences- only jute, only glass, glass, and jute alternatively (g/j/g/j---) and 4 glass - 9 jute – 4 glass (4g-9j-4g). The fabricated composite panels are analyzed through fiber volume calculation, tensile test, bending test, and water absorption test. The hybridization of jute and glass fiber results in better tensile, bending, and water absorption properties than only jute fiber-reinforced composites, but inferior properties as compared to only glass fiber reinforced composites. Among different fiber layering sequences, 4g-9j-4g fibers layering sequence resulted in better tensile, bending, and water absorption properties. The effect of chemical treatment on the woven jute fiber and chopped glass microfiber infusion are also investigated in this study. Chemically treated jute fiber and 2 wt. % chopped glass microfiber infused hybrid composite shows about 12% improvements in flexural strength as compared to untreated and no micro-fiber infused hybrid composite panel. However, fiber chemical treatment and micro-filler do not have a significant effect on tensile strength.

Keywords: compression molding, chemical treatment, hybrid composites, mechanical properties

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714 Mott Transition in the VO2/LSCO Heterojunction

Authors: Yi Hu, Chun-Chi Lin, Shau-En Yeh, Shin Lee

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In this study, p–n heterojunctions with La0.5Sr0.5CoO3 (LSCO) and W-doped VO2 thin films were fabricated by the radio frequency (r.f.) magnetron sputtering technique and sol-gel process, respectively. The thickness of VO2 and LSCO thin films are about 40 nm and 400 nm, respectively. Good crystalline match between LSCO and VO2 films was observed from the SEM. The built-in voltages for the junction are about 1.1 V and 2.3 V for the sample in the metallic and insulating state, respectively. The sample can undergo the current induced MIT during applying field when the sample was heated at 40 and 50ºC. This is in agreement with the value obtained from the difference in the work functions of LSCO and VO2. The band structure of the heterojunction was proposed based on the results of analysis.

Keywords: hetrojection, Mott transition, switching , VO2

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713 Dynamic of an Invasive Insect Gut Microbiome When Facing to Abiotic Stress

Authors: Judith Mogouong, Philippe Constant, Robert Lavallee, Claude Guertin

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The emerald ash borer (EAB) is an exotic wood borer insect native from China, which is associated with important environmental and economic damages in North America. Beetles are known to be vectors of microbial communities related to their adaptive capacities. It is now established that environmental stress factors may induce physiological events on the host trees, such as phytochemical changes. Consequently, that may affect the establishment comportment of herbivorous insect. Considering the number of insects collected on ash trees (insects’ density) as an abiotic factor related to stress damage, the aim of our study was to explore the dynamic of EAB gut microbial community genome (microbiome) when facing that factor and to monitor its diversity. Insects were trapped using specific green Lindgren© traps. A gradient of the captured insect population along the St. Lawrence River was used to create three levels of insects’ density (low, intermediate, and high). After dissection, total DNA extracted from insect guts of each level has been sent for amplicon sequencing of bacterial 16S rRNA gene and fungal ITS2 region. The composition of microbial communities among sample appeared largely diversified with the Simpson index significantly different across the three levels of density for bacteria. Add to that; bacteria were represented by seven phyla and twelve classes, whereas fungi were represented by two phyla and seven known classes. Using principal coordinate analysis (PCoA) based on Bray Curtis distances of 16S rRNA sequences, we observed a significant variation between the structure of the bacterial communities depending on insects’ density. Moreover, the analysis showed significant correlations between some bacterial taxa and the three classes of insects’ density. This study is the first to present a complete overview of the bacterial and fungal communities associated with the gut of EAB base on culture-independent methods, and to correlate those communities with a potential stress factor of the host trees.

Keywords: gut microbiome, DNA, 16S rRNA sequences, emerald ash borer

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712 Digital Control Techniques for Power Electronic Devices

Authors: Rakesh Krishna, Abhishek Poddar

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The paper discusses the work carried out on the implementation of control techniques like Digital Pulse Width Modulation (PWM) and Digital Pulse Fired control(PFC). These techniques are often used in devices like inverters, battery chargers, DC-to-DC converters can also be implemented on household devices like heaters. The advantage being the control and improved life span of device. In case of batteries using these techniques are known to increase the life span of battery in mobiles and other hand-held devices. 8051 microcontroller is used to implement these methods.Thyristors are used for switching operations.

Keywords: PWM, SVM, PFC, bidirectional inverters, snubber

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711 Exploring Emerging Viruses From a Protected Reserve

Authors: Nemat Sokhandan Bashir

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Threats from viruses to agricultural crops could be even larger than the losses caused by the other pathogens because, in many cases, the viral infection is latent but crucial from an epidemic point of view. Wild vegetation can be a source of many viruses that eventually find their destiny in crop plants. Although often asymptomatic in wild plants due to adaptation, they can potentially cause serious losses in crops. Therefore, exploring viruses in wild vegetation is very important. Recently, omics have been quite useful for exploring plant viruses from various plant sources, especially wild vegetation. For instance, we have discovered viruses such as Ambrossia asymptomatic virus I (AAV-1) through the application of metagenomics from Oklahoma Prairie Reserve. Accordingly, extracts from randomly-sampled plants are subjected to high speed and ultracentrifugation to separated virus-like particles (VLP), then nucleic acids in the form of DNA or RNA are extracted from such VLPs by treatment with phenol—chloroform and subsequent precipitation by ethanol. The nucleic acid preparations are separately treated with RNAse or DNAse in order to determine the genome component of VLPs. In the case of RNAs, the complementary cDNAs are synthesized before submitting to DNA sequencing. However, for VLPs with DNA contents, the procedure would be relatively straightforward without making cDNA. Because the length of the nucleic acid content of VPLs can be different, various strategies are employed to achieve sequencing. Techniques similar to so-called "chromosome walking" may be used to achieve sequences of long segments. When the nucleotide sequence data were obtained, they were subjected to BLAST analysis to determine the most related previously reported virus sequences. In one case, we determined that the novel virus was AAV-l because the sequence comparison and analysis revealed that the reads were the closest to the Indian citrus ringspot virus (ICRSV). AAV—l had an RNA genome with 7408 nucleotides in length and contained six open reading frames (ORFs). Based on phylogenies inferred from the replicase and coat protein ORFs of the virus, it was placed in the genus Mandarivirus.

Keywords: wild, plant, novel, metagenomics

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710 The Impact of Small-Scale Irrigation on the Income of Rural Households and Determinants of Its Adoption: Evidence from Dehana Woreda, Ethiopia

Authors: Wondmnew Derebe Yohannis

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Farming irrigation plays a crucial role in rural development strategies, impacting both annual household income and livelihood. This research aims to evaluate the factors influencing irrigation participation and assess the impact of small-scale irrigation on rural households' annual income. The study collected data from 287 farmers in the Dahana district of northern Ethiopia. The research investigates the driving forces behind farmers' decisions to adopt small-scale irrigation and its effect on annual income gain. The findings reveal that several factors positively influence the probability of adoption, including access to credit, cultivated land size, livestock holding, extension contact, and the education level of the household head. Conversely, the distance to local markets and water schemes negatively affects the likelihood of adoption. To understand the differences in annual income between farm households that adopted irrigation and those that did not, a simultaneous equations model with endogenous switching regression is estimated. This accounts for the heterogeneity in the adoption decision and unobservable characteristics of farmers and their farms. The analysis compares the expected income gain under actual and counterfactual scenarios, considering whether the farm household adopted irrigation or not. The study reveals that the group of farm households that adopted irrigation has distinct characteristics compared to those that did not adopt it. Furthermore, the research demonstrates that the adoption of irrigation practices leads to an increase in annual income. Interestingly, the impact of small-scale irrigation on annual income is greater for the farm households that actually adopted irrigation compared to those in the counterfactual scenario where they did not adopt. Based on the findings, the researcher concludes that small-scale irrigation is a practical solution for meeting household financial needs in the study area. It is recommended that investments in small-scale irrigation continue to further improve the livelihoods of rural farming communities by enhancing annual income gains.

Keywords: small-scale irrigation, income, rural farm households, endogenous switching regression, user, non-user

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709 A Long Short-Term Memory Based Deep Learning Model for Corporate Bond Price Predictions

Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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708 Tectono-Stratigraphic Architecture, Depositional Systems and Salt Tectonics to Strike-Slip Faulting in Kribi-Campo-Cameroon Atlantic Margin with an Unsupervised Machine Learning Approach (West African Margin)

Authors: Joseph Bertrand Iboum Kissaaka, Charles Fonyuy Ngum Tchioben, Paul Gustave Fowe Kwetche, Jeannette Ngo Elogan Ntem, Joseph Binyet Njebakal, Ribert Yvan Makosso-Tchapi, François Mvondo Owono, Marie Joseph Ntamak-Nida

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Located in the Gulf of Guinea, the Kribi-Campo sub-basin belongs to the Aptian salt basins along the West African Margin. In this paper, we investigated the tectono-stratigraphic architecture of the basin, focusing on the role of salt tectonics and strike-slip faults along the Kribi Fracture Zone with implications for reservoir prediction. Using 2D seismic data and well data interpreted through sequence stratigraphy with integrated seismic attributes analysis with Python Programming and unsupervised Machine Learning, at least six second-order sequences, indicating three main stages of tectono-stratigraphic evolution, were determined: pre-salt syn-rift, post-salt rift climax and post-rift stages. The pre-salt syn-rift stage with KTS1 tectonosequence (Barremian-Aptian) reveals a transform rifting along NE-SW transfer faults associated with N-S to NNE-SSW syn-rift longitudinal faults bounding a NW-SE half-graben filled with alluvial to lacustrine-fan delta deposits. The post-salt rift-climax stage (Lower to Upper Cretaceous) includes two second-order tectonosequences (KTS2 and KTS3) associated with the salt tectonics and Campo High uplift. During the rift-climax stage, the growth of salt diapirs developed syncline withdrawal basins filled by early forced regression, mid transgressive and late normal regressive systems tracts. The early rift climax underlines some fine-grained hangingwall fans or delta deposits and coarse-grained fans from the footwall of fault scarps. The post-rift stage (Paleogene to Neogene) contains at least three main tectonosequences KTS4, KTS5 and KTS6-7. The first one developed some turbiditic lobe complexes considered as mass transport complexes and feeder channel-lobe complexes cutting the unstable shelf edge of the Campo High. The last two developed submarine Channel Complexes associated with lobes towards the southern part and braided delta to tidal channels towards the northern part of the Kribi-Campo sub-basin. The reservoir distribution in the Kribi-Campo sub-basin reveals some channels, fan lobes reservoirs and stacked channels reaching up to the polygonal fault systems.

Keywords: tectono-stratigraphic architecture, Kribi-Campo sub-basin, machine learning, pre-salt sequences, post-salt sequences

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707 Implementation of Traffic Engineering Using MPLS Technology

Authors: Vishal H. Shukla, Sanjay B. Deshmukh

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Traffic engineering, at its center, is the ability of moving traffic approximately so that traffic from a congested link is moved onto the unused capacity on another link. Traffic Engineering ensures the best possible use of the resources. Now to support traffic engineering in the today’s network, Multiprotocol Label Switching (MPLS) is being used which is very helpful for reliable packets delivery in an ongoing internet services. Here a topology is been implemented on GNS3 to focus on the analysis of the communication take place from one site to other through the ISP. The comparison is made between the IP network & MPLS network based on Bandwidth & Jitter which are one of the performance parameters using JPERF simulator.

Keywords: GNS3, JPERF, MPLS, traffic engineering, VMware

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706 The Effect of Extensive Mosquito Migration on Dengue Control as Revealed by Phylogeny of Dengue Vector Aedes aegypti

Authors: M. D. Nirmani, K. L. N. Perera, G. H. Galhena

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Dengue has become one of the most important arbo-viral disease in all tropical and subtropical regions of the world. Aedes aegypti, is the principal vector of the virus, vary in both epidemiological and behavioral characteristics, which could be finely measured through DNA sequence comparison at their population level. Such knowledge in the population differences can assist in implementation of effective vector control strategies allowing to make estimates of the gene flow and adaptive genomic changes, which are important predictors of the spread of Wolbachia infection or insecticide resistance. As such, this study was undertaken to investigate the phylogenetic relationships of Ae. aegypti from Galle and Colombo, Sri Lanka, based on the ribosomal protein region which spans between two exons, in order to understand the geographical distribution of genetically distinct mosquito clades and its impact on mosquito control measures. A 320bp DNA region spanning from 681-930 bp, corresponding to the ribosomal protein, was sequenced in 62 Ae. aegypti larvae collected from Galle (N=30) and Colombo (N=32), Sri Lanka. The sequences were aligned using ClustalW and the haplotypes were determined with DnaSP 5.10. Phylogenetic relationships among haplotypes were constructed using the maximum likelihood method under Tamura 3 parameter model in MEGA 7.0.14 including three previously reported sequences of Australian (N=2) and Brazilian (N=1) Ae. aegypti. The bootstrap support was calculated using 1000 replicates and the tree was rooted using Aedes notoscriptus (GenBank accession No. KJ194101). Among all sequences, nineteen different haplotypes were found among which five haplotypes were shared between 80% of mosquitoes in the two populations. Seven haplotypes were unique to each of the population. Phylogenetic tree revealed two basal clades and a single derived clade. All observed haplotypes of the two Ae. aegypti populations were distributed in all the three clades, indicating a lack of genetic differentiation between populations. The Brazilian Ae. aegypti haplotype and one of the Australian haplotypes were grouped together with the Sri Lankan basal haplotype in the same basal clade, whereas the other Australian haplotype was found in the derived clade. Phylogram showed that Galle and Colombo Ae. aegypti populations are highly related to each other despite the large geographic distance (129 Km) indicating a substantial genetic similarity between them. This may have probably arisen from passive migration assisted by human travelling and trade through both land and water as the two areas are bordered by the sea. In addition, studied Sri Lankan mosquito populations were closely related to Australian and Brazilian samples. Probably this might have caused by shipping industry between the three countries as all of them are fully or partially enclosed by sea. For example, illegal fishing boats migrating to Australia by sea is perhaps a good mean of transportation of all life stages of mosquitoes from Sri Lanka. These findings indicate that extensive mosquito migrations occur between populations not only within the country, but also among other countries in the world which might be a main barrier to the successful vector control measures.

Keywords: Aedes aegypti, dengue control, extensive mosquito migration, haplotypes, phylogeny, ribosomal protein

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705 A Nucleic Acid Extraction Method for High-Viscosity Floricultural Samples

Authors: Harunori Kawabe, Hideyuki Aoshima, Koji Murakami, Minoru Kawakami, Yuka Nakano, David D. Ordinario, C. W. Crawford, Iri Sato-Baran

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With the recent advances in gene editing technologies allowing the rewriting of genetic sequences, additional market growth in the global floriculture market beyond previous trends is anticipated through increasingly sophisticated plant breeding techniques. As a prerequisite for gene editing, the gene sequence of the target plant must first be identified. This necessitates the genetic analysis of plants with unknown gene sequences, the extraction of RNA, and comprehensive expression analysis. Consequently, a technology capable of consistently and effectively extracting high-purity DNA and RNA from plants is of paramount importance. Although model plants, such as Arabidopsis and tobacco, have established methods for DNA and RNA extraction, floricultural species such as roses present unique challenges. Different techniques to extract DNA and RNA from various floricultural species were investigated. Upon sampling and grinding the petals of several floricultural species, it was observed that nucleic acid extraction from the ground petal solutions of low viscosity was straightforward; solutions of high viscosity presented a significant challenge. It is postulated that the presence of substantial quantities of polysaccharides and polyphenols in the plant tissue was responsible for the inhibition of nucleic acid extraction. Consequently, attempts were made to extract high-purity DNA and RNA by improving the CTAB method and combining it with commercially available nucleic acid extraction kits. The quality of the total extracted DNA and RNA was evaluated using standard methods. Finally, the effectiveness of the extraction method was assessed by determining whether it was possible to create a library that could be applied as a suitable template for a next-generation sequencer. In conclusion, a method was developed for consistent and accurate nucleic acid extraction from high-viscosity floricultural samples. These results demonstrate improved techniques for DNA and RNA extraction from flowers, help facilitate gene editing of floricultural species and expand the boundaries of research and commercial opportunities.

Keywords: floriculture, gene editing, next-generation sequencing, nucleic acid extraction

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704 Design and Implementation of Grid-Connected Photovoltaic Inverter

Authors: B. H. Lee

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Nowadays, a grid-connected photovoltaic (PV) inverter is adopted in various places like as home, factory, because grid-connected PV inverter can reduce total power consumption by supplying electricity from PV array. In this paper, design and implementation of a 300 W grid-connected PV inverter are described. It is implemented with TI Piccolo DSP core and operated at 100 kHz switching frequency in order to reduce harmonic contents. The maximum operating input voltage is up to 45 V. The characteristics of the designed system that include maximum power point tracking (MPPT), single operation and battery charging are verified by simulation and experimental results.

Keywords: design, grid-connected, implementation, photovoltaic

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703 In Vitro Studies on Antimicrobial Activities of Lactic Acid Bacteria Isolated from Fresh Fruits for Biocontrol of Pathogens

Authors: Okolie Pius Ifeanyi, Emerenini Emilymary Chima

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Aims: The study investigated the diversity and identities of Lactic Acid Bacteria (LAB) isolated from different fresh fruits using Molecular Nested PCR analysis and the efficacy of cell free supernatants from Lactic Acid Bacteria (LAB) isolated from fresh fruits for in vitro control of some tomato pathogens. Study Design: Nested PCR approach was used in this study employing universal 16S rRNA gene primers in the first round PCR and LAB specific Primers in the second round PCR with the view of generating specific Nested PCR products for the LAB diversity present in the samples. The inhibitory potentials of supernatant obtained from LAB isolates of fruits origin that were molecularly characterized were investigated against some tomato phytopathogens using agar-well method with the view to develop biological agents for some tomato disease causing organisms. Methodology: Gram positive, catalase negative strains of LAB were isolated from fresh fruits on Man Rogosa and Sharpe agar (Lab M) using streaking method. Isolates obtained were molecularly characterized by means of genomic DNA extraction kit (Norgen Biotek, Canada) method. Standard methods were used for Nested Polymerase Chain Reaction (PCR) amplification targeting the 16S rRNA gene using universal 16S rRNA gene and LAB specific primers, agarose gel electrophoresis, purification and sequencing of generated Nested PCR products (Macrogen Inc., USA). The partial sequences obtained were identified by blasting in the non-redundant nucleotide database of National Center for Biotechnology Information (NCBI). The antimicrobial activities of characterized LAB against some tomato phytopathogenic bacteria which include (Xanthomonas campestries, Erwinia caratovora, and Pseudomonas syringae) were obtained by using the agar well diffusion method. Results: The partial sequences obtained were deposited in the database of National Centre for Biotechnology Information (NCBI). Isolates were identified based upon the sequences as Weissella cibaria (4, 18.18%), Weissella confusa (3, 13.64%), Leuconostoc paramensenteroides (1, 4.55%), Lactobacillus plantarum (8, 36.36%), Lactobacillus paraplantarum (1, 4.55%) and Lactobacillus pentosus (1, 4.55%). The cell free supernatants of LAB from fresh fruits origin (Weissella cibaria, Weissella confusa, Leuconostoc paramensenteroides, Lactobacillus plantarum, Lactobacillus paraplantarum and Lactobacillus pentosus) can inhibits these bacteria by creating clear zones of inhibition around the wells containing cell free supernatants of the above mentioned strains of lactic acid bacteria. Conclusion: This study shows that potentially LAB can be quickly characterized by molecular methods to specie level by nested PCR analysis of the bacteria isolate genomic DNA using universal 16S rRNA primers and LAB specific primer. Tomato disease causing organisms can be most likely biologically controlled by using extracts from LAB. This finding will reduce the potential hazard from the use of chemical herbicides on plant.

Keywords: nested pcr, molecular characterization, 16s rRNA gene, lactic acid bacteria

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702 Characterization of Fungal Endophytes in Leaves, Stems and Roots of African Yam Bean (Sphenostylis sternocarpa Hochst ex. A. Rich Harms)

Authors: Iyabode A. Kehinde, Joshua O. Oyekanmi, Jumoke T. Abimbola, Olajumoke E. Ayanda

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African yam bean (AYB), (Sphenostylis stenocarpa) is a leguminous crop that provides nutritionally rich seeds, tubers and leaves for human consumption. AYB potentials as an important food security crop is yet to be realized and thus classified as underutilized crop. Underutilization of the crop has been partly associated with scarce information on the incidence and characterization of fungal endophytes infecting vascular parts of AYB. Accurate and robust detection of these endophytic fungi is essential for diagnosis, modeling, surveillance and protection of germplasm (seed) health. This work aimed at isolating and identifying fungal endophytes associated with leaves, stems and roots of AYB in Ogun State, Nigeria. This study investigated both cultural and molecular properties of endophytic fungi in AYB for its characterization and diversity. Fungal endophytes were isolated and culturally identified. DNA extraction, PCR amplification using ITS primers and analyses of nucleotide sequences of ribosomal DNA fragments were conducted on selected isolates. BLAST analysis was conducted on consensus nucleotide sequences of 28 out of 30 isolates and results showed similar homology with genera of Rhizopus, Cunninghamella, Fusarium, Aspergillus, Penicillium, Alternaria, Diaporthe, Nigrospora, Purpureocillium, Corynespora, Magnaporthe, Macrophomina, Curvularia, Acrocalymma, Talaromyces and Simplicillium. Slight similarity was found with endophytes associated with soybean. Phylogenetic analysis by maximum likelihood method showed high diversity among the general. These organisms have high economic importance in crop improvement. For an instance, Purpureocillium lilacinum showed high potential in control of root rot caused by nematodes in tomatoes. Though some can be pathogens, but many of the fungal endophytes have beneficial attributes to plant in host health, uptake of nutrients, disease suppression, and host immunity.

Keywords: molecular characterization, African Yam Bean, fungal endophyte, plant parts

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701 The Istrian Istrovenetian-Croatian Bilingual Corpus

Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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700 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 164
699 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 153
698 Cellular RNA-Binding Domains with Distant Homology in Viral Proteomes

Authors: German Hernandez-Alonso, Antonio Lazcano, Arturo Becerra

Abstract:

Until today, viruses remain controversial and poorly understood; about their origin, this problem represents an enigma and one of the great challenges for the contemporary biology. Three main theories have tried to explain the origin of viruses: regressive evolution, escaped host gene, and pre-cellular origin. Under the perspective of the escaped host gene theory, it can be assumed a cellular origin of viral components, like protein RNA-binding domains. These universal distributed RNA-binding domains are related to the RNA metabolism processes, including transcription, processing, and modification of transcripts, translation, RNA degradation and its regulation. In the case of viruses, these domains are present in important viral proteins like helicases, nucleases, polymerases, capsid proteins or regulation factors. Therefore, they are implicated in the replicative cycle and parasitic processes of viruses. That is why it is possible to think that those domains present low levels of divergence due to selective pressures. For these reasons, the main goal for this project is to create a catalogue of the RNA-binding domains found in all the available viral proteomes, using bioinformatics tools in order to analyze its evolutionary process, and thus shed light on the general virus evolution. ProDom database was used to obtain larger than six thousand RNA-binding domain families that belong to the three cellular domains of life and some viral groups. From the sequences of these families, protein profiles were created using HMMER 3.1 tools in order to find distant homologous within greater than four thousand viral proteomes available in GenBank. Once accomplished the analysis, almost three thousand hits were obtained in the viral proteomes. The homologous sequences were found in proteomes of the principal Baltimore viral groups, showing interesting distribution patterns that can contribute to understand the evolution of viruses and their host-virus interactions. Presence of cellular RNA-binding domains within virus proteomes seem to be explained by closed interactions between viruses and their hosts. Recruitment of these domains is advantageous for the viral fitness, allowing viruses to be adapted to the host cellular environment.

Keywords: bioinformatics tools, distant homology, RNA-binding domains, viral evolution

Procedia PDF Downloads 385
697 Finite Element Analysis of Debonding Propagation in FM73 Joint under Static Loading

Authors: Reza Hedayati, Meysam Jahanbakhshi

Abstract:

In this work, Fracture Mechanics is used to predict crack propagation in the adhesive joining aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore, 2*3=6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases.

Keywords: adhesive joint, debonding, fracture, LEFM, APDL

Procedia PDF Downloads 587
696 Human Gait Recognition Using Moment with Fuzzy

Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

Procedia PDF Downloads 754
695 Prediction of Crack Propagation in Bonded Joints Using Fracture Mechanics

Authors: Reza Hedayati, Meysam Jahanbakhshi

Abstract:

In this work, Fracture Mechanics is used to predict crack propagation in the adhesive jointing aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore 2*3=6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases.

Keywords: fracture, adhesive joint, debonding, APDL, LEFM

Procedia PDF Downloads 409
694 Primes as Sums and Differences of Two Binomial Coefficients and Two Powersums

Authors: Benjamin Lee Warren

Abstract:

Many problems exist in additive number theory which is essential to determine the primes that are the sum of two elements from a given single-variable polynomial sequence, and most of them are unattackable in the present day. Here, we determine solutions for this problem to a few certain sequences (certain binomial coefficients and power sums) using only elementary algebra and some algebraic factoring methods (as well as Euclid’s Lemma and Faulhaber’s Formula). In particular, we show that there are finitely many primes as sums of two of these types of elements. Several cases are fully illustrated, and bounds are presented for the cases not fully illustrated.

Keywords: binomial coefficients, power sums, primes, algebra

Procedia PDF Downloads 98
693 Assessment the Quality of Telecommunication Services by Fuzzy Inferences System

Authors: Oktay Nusratov, Ramin Rzaev, Aydin Goyushov

Abstract:

Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IP-protocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network.

Keywords: quality of communication, IP-telephony, fuzzy set, fuzzy implication, neural network

Procedia PDF Downloads 466
692 Heritage Spanish Speaker’s Bilingual Practices and Linguistic Varieties: Challenges and Opportunities

Authors: Ana C. Sanchez

Abstract:

This paper will discuss some of the bilingual practices of Heritage Spanish speakers caused by living within two cultures and two languages, Spanish, the heritage language, and English, the dominant language. When two languages remain in contact for long periods, such as the case of Spanish and English, it is common that both languages can be affected by bilingual practices such as Spanglish, code-switching, borrowing, anglicisms and calques. Examples of these translingual practices will be provided, as well as HS speaker’s linguistic dialects, and the challenges they encounter with the standard variety used in the Spanish classroom.

Keywords: heritage, practices, Spanish, speakers translingual

Procedia PDF Downloads 197
691 Probabilistic Modeling Laser Transmitter

Authors: H. S. Kang

Abstract:

Coupled electrical and optical model for conversion of electrical energy into coherent optical energy for transmitter-receiver link by solid state device is presented. Probability distribution for travelling laser beam switching time intervals and the number of switchings in the time interval is obtained. Selector function mapping is employed to regulate optical data transmission speed. It is established that regulated laser transmission from PhotoActive Laser transmitter follows principal of invariance. This considerably simplifies design of PhotoActive Laser Transmission networks.

Keywords: computational mathematics, finite difference Markov chain methods, sequence spaces, singularly perturbed differential equations

Procedia PDF Downloads 428
690 Fractional-Order Modeling of GaN High Electron Mobility Transistors for Switching Applications

Authors: Anwar H. Jarndal, Ahmed S. Elwakil

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In this paper, a fraction-order model for pad parasitic effect of GaN HEMT on Si substrate is developed and validated. Open de-embedding structure is used to characterize and de-embed substrate loading parasitic effects. Unbiased device measurements are implemented to extract parasitic inductances and resistances. The model shows very good simulation for S-parameter measurements under different bias conditions. It has been found that this approach can improve the simulation of intrinsic part of the transistor, which is very important for small- and large-signal modeling process.

Keywords: fractional-order modeling, GaNHEMT, si-substrate, open de-embedding structure

Procedia PDF Downloads 350
689 Unzipping the Stress Response Genes in Moringa oleifera Lam. through Transcriptomics

Authors: Vivian A. Panes, Raymond John S. Rebong, Miel Q. Diaz

Abstract:

Moringa oleifera Lam. is known mainly for its high nutritional value and medicinal properties contributing to its popular reputation as a 'miracle plant' in the tropical climates where it usually grows. The main objective of this study is to discover the genes and gene products involved in abiotic stress-induced activity that may impact the M. oleifera Lam. mature seeds as well as their corresponding functions. In this study, RNA-sequencing and de novo transcriptome assembly were performed using two assemblers, Trinity and Oases, which produced 177,417 and 120,818 contigs respectively. These transcripts were then subjected to various bioinformatics tools such as Blast2GO, UniProt, KEGG, and COG for gene annotation and the analysis of relevant metabolic pathways. Furthermore, FPKM analysis was performed to identify gene expression levels. The sequences were filtered according to the 'response to stress' GO term since this study dealt with stress response. Clustered Orthologous Groups (COG) showed that the highest frequencies of stress response gene functions were those of cytoskeleton which make up approximately 14% and 23% of stress-related sequences under Trinity and Oases respectively, recombination, repair and replication at 11% and 14% respectively, carbohydrate transport and metabolism at 23% and 9% respectively and defense mechanisms 16% and 12% respectively. KEGG pathway analysis determined the most abundant stress-response genes in the phenylpropanoid biosynthesis at counts of 187 and 166 pathways for Oases and Trinity respectively, purine metabolism at 123 and 230 pathways, and biosynthesis of antibiotics at 105 and 102. Unique and cumulative GO term counts revealed that majority of the stress response genes belonged to the category of cellular response to stress at cumulative counts of 1,487 to 2,187 for Oases and Trinity respectively, defense response at 754 and 1,255, and response to heat at 213 and 208, response to water deprivation at 229 and 228, and oxidative stress at 508 and 488. Lastly, FPKM was used to determine the levels of expression of each stress response gene. The most upregulated gene encodes for thiamine thiazole synthase chloroplastic-like enzyme which plays a significant role in DNA damage tolerance. Data analysis implies that M. oleifera stress response genes are directed towards the effects of climate change more than other stresses indicating the potential of M. oleifera for cultivation in harsh environments because it is resistant to climate change, pathogens, and foreign invaders.

Keywords: stress response, genes, Moringa oleifera, transcriptomics

Procedia PDF Downloads 143
688 Using the Smith-Waterman Algorithm to Extract Features in the Classification of Obesity Status

Authors: Rosa Figueroa, Christopher Flores

Abstract:

Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

Procedia PDF Downloads 293
687 Semirings of Graphs: An Approach Towards the Algebra of Graphs

Authors: Gete Umbrey, Saifur Rahman

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Graphs are found to be most capable in computing, and its abstract structures have been applied in some specific computations and algorithms like in phase encoding controller, processor microcontroller, and synthesis of a CMOS switching network, etc. Being motivated by these works, we develop an independent approach to study semiring structures and various properties by defining the binary operations which in fact, seems analogous to an existing definition in some sense but with a different approach. This work emphasizes specifically on the construction of semigroup and semiring structures on the set of undirected graphs, and their properties are investigated therein. It is expected that the investigation done here may have some interesting applications in theoretical computer science, networking and decision making, and also on joining of two network systems.

Keywords: graphs, join and union of graphs, semiring, weighted graphs

Procedia PDF Downloads 145