Search results for: simple sequence repeat (SSR)

Authors: R. Sulakshana, R. Lakshmi

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Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR associate (CRISPR/Cas) is an adaptive immunity system found in bacteria and archaea. It has been modified to serve as a potent gene editing tool. Moreover, it has found widespread use in the field of genome research because of its accessibility and low cost. Several bioinformatics methods have been created to aid in the construction of specific single guide RNA (sgRNA), which is highly active and crucial to CRISPR/Cas performance. Various Cas proteins, including Cas1, Cas2, Cas9, and Cas12, have been used to create genome engineering tools because of their programmable sequence specificity. Class 1 and 2 CRISPR/Cas systems, as well as the processes of all known Cas proteins (including Cas9 and Cas12), are discussed in this review paper. In addition, the various CRISPR methodologies and their tools so far discovered are discussed. Finally, the challenges and issues in the CRISPR system along with future works, are presented.

Keywords: gene editing tool, Cas proteins, CRISPR, guideRNA, programmable sequence

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Authors: Eun-Ji Lee, Hye-Sung Park, Chan-Jung Lee, Won-Sik Kong

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We analyzed the DNA sequence of the ITS (Internal Transcribed Spacer) region of the 18S ribosomal gene and compared it with the gene sequence of T. fuciformis and Hypoxylon sp. in the BLAST database. The sequences of collected T. fuciformis and Hypoxylon sp. have over 99% homology in the T. fuciformis and Hypoxylon sp. sequence BLAST database. In order to select the optimal medium for T. fuciformis, five kinds of a medium such as Potato Dextrose Agar (PDA), Mushroom Complete Medium (MCM), Malt Extract Agar (MEA), Yeast extract (YM), and Compost Extract Dextrose Agar (CDA) were used. T. fuciformis showed the best growth on PDA medium, and Hypoxylon sp. showed the best growth on MCM. So as to investigate the optimum pH and temperature, the pH range was set to pH4 to pH8 and the temperature range was set to 15℃ to 35℃ (5℃ degree intervals). Optimum culture conditions for the T. fuciformis growth were pH5 at 25℃. Hypoxylon sp. were pH6 at 25°C. In order to confirm the most suitable carbon source, we used fructose, galactose, saccharose, soluble starch, inositol, glycerol, xylose, dextrose, lactose, dextrin, Na-CMC, adonitol. Mannitol, mannose, maltose, raffinose, cellobiose, ethanol, salicine, glucose, arabinose. In the optimum carbon source, T. fuciformis is xylose and Hypoxylon sp. is arabinose. Using the column test, we confirmed sawdust a suitable for T. fuciformis, since the composition of sawdust affects the growth of fruiting bodies of T. fuciformis. The sawdust we used is oak tree, pine tree, poplar, birch, cottonseed meal, cottonseed hull. In artificial cultivation of T. fuciformis with sawdust medium, T. fuciformis and Hypoxylon sp. showed fast mycelial growth on mixture of oak tree sawdust, cottonseed hull, and wheat bran.

Keywords: cultivation, optimal condition, tremella fuciformis, nutritional source

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Leyla Esfandiari

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Rapid, sensitive detection of nucleic acid (NA) molecules of specific sequence is of interest for a range of diverse health-related applications such as screening for genetic diseases, detecting pathogenic microbes in food and water, and identifying biological warfare agents in homeland security. Sequence-specific nucleic acid detection platforms rely on base pairing interaction between two complementary single stranded NAs, which can be detected by the optical, mechanical, or electrochemical readout. However, many of the existing platforms require amplification by polymerase chain reaction (PCR), fluorescent or enzymatic labels, and expensive or bulky instrumentation. In an effort to address these shortcomings, our research is focused on utilizing the cutting edge nanotechnology and microfluidics along with resistive pulse electrical measurements to design and develop a cost-effective, handheld and highly-sensitive nanopore-based sensor for point-of-care medical diagnostics.

Keywords: diagnostics, nanopore, nucleic acids, sensor

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Patrascu Andrei Tudor

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One of the main problems in high energy physics is the fact that we do not have a complete understanding of the interaction between local and global effects in gauge theory. This has an increasing impact on our ability to access the non-perturbative regime of most of our theories. Our theories, while being based on gauge groups considered to be simple or semi-simple and connected, are expected to be described by their simple local linear approximation, namely the Lie algebras. However, higher homotopy properties resulting in gauge anomalies appear frequently in theories of physical interest. Our assumption that the groups we deal with are simple and simply connected is probably not suitable, and ways to go beyond such assumptions, particularly in gauge theories, where the Lie algebra linear approximation is prevalent, are not known. We approach this problem from two directions: on one side we are explaining the potential role of formal group laws in describing certain higher homotopical properties and interferences with local or perturbative effects, and on the other side, we employ a categorical approach leading to synthetic theory and a way of looking at gauge theories. The topos approach is based on a geometry where the fundamental logic is intuitionistic logic, and hence the ‘tertium non datur’ principle is abandoned. This has a remarkable impact on understanding conformal symmetry and its anomalies in string theory in various dimensions.

Keywords: Gauge theory, formal group laws, Topos theory, conformal symmetry

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Authors: Valeria M. Bastos, Myrian A. Costa, Matheus Ambrozio, Nelson F. F. Ebecken

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In this paper a very simple and effective user administration view of computing clusters systems is implemented in order of friendly provide the configuration and monitoring of distributed application executions. The user view, the administrator view, and an internal control module create an illusionary management environment for better system usability. The architecture, properties, performance, and the comparison with others software for cluster management are briefly commented.

Keywords: big data, computing clusters, administration view, user view

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Authors: Mandeep Singh Azad.Dibyendu Chakraborty, Vikas Vohra

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Introduction: Poonch is one of the remotest districts of the Jammu and Kashmir (UT) and situated on international borders. This native poultry population in these areas is quite hardy and thrives well in adverse climatic conditions. Till date, no local breed from this area (Jammu Province) has been characterized thus present study was undertaken with the main objectives of molecular characterization of ChB6 gene in local native chicken of Poonch region located at international borders between India and Pakistan. The chicken B-cell marker (ChB6) gene has been proposed as a candidate gene in regulating B-cell development. Material and Method: RNA was isolated by Blood RNA Purification Kit (HiPura) and Trizol method from whole blood samples. Positive PCR products with size 1110 bp were selected for further purification, sequencing and analysis. The amplified PCR product was sequenced by Sangers dideoxy chain termination method. The obtained sequence of ChB6 gene of Poonchi chicken were compared by MEGAX software. BioEdit software was used to construct phylogenic tree, and Neighbor Joining method was used to infer evolutionary history. In order to compute evolutionary distance Maximum Composite Likelihood method was used. Results: The positively amplified samples of ChB6 genes were then subjected to Sanger sequencing with “Primer Walking. The sequences were then analyzed using MEGA X and BioEdit software. The sequence results were compared with other reported sequence from different breed of chicken and with other species obtained from the NCBI (National Center for Biotechnology Information). ClustalW method using MEGA X software was used for multiple sequence alignment. The sequence results of ChB6 gene of Poonchi chicken was compared with Centrocercus urophasianus, G. gallus mRNA for B6.1 protein, G. gallus mRNA for B6.2, G. gallus mRNA for B6.3, Gallus gallus B6.1, Halichoeres bivittatus, Miniopterus fuliginosus Ferringtonia patagonica, Tympanuchus phasianellus. The genetic distances were 0.2720, 0.0000, 0.0245, 0.0212, 0.0147, 1.6461, 2.2394, 2.0070 and 0.2363 for ChB6 gene of Poonchi chicken sequence with other sequences in the present study respectively. Sequencing results showed variations between different species. It was observed that AT content were higher then GC content for ChB6 gene. The lower AT content suggests less thermostable. It was observed that there was no sequence difference within the Poonchi population for ChB6 gene. The high homology within chicken population indicates the conservation of ChB6 gene. The maximum difference was observed with Miniopterus fuliginosus (Eastern bent-wing bat) followed by Ferringtonia patagonica and Halichoeres bivittatus. Conclusion: Genetic variation is the essential component for genetic improvement. The results of immune related gene Chb6 shows between population genetic variability. Therefore, further association studies of this gene with some prevalent diseases in large population would be helpful to identify disease resistant/ susceptible genotypes in the indigenous chicken population.

Keywords: ChB6, sequencing, ClustalW, genetic distance, poonchi chicken, SNP

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Authors: Kukuri Tavartkiladze, Nana Bolashvili

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The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Keywords: aridity, climate change, desertification, precipitation

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Authors: Mahdi Golriz

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The aim of this work is to estimate the change in molecular structure of linear low-density polyethylene (LLDPE) during peroxide modification can be detected by a simple rheological method. For this purpose a commercial grade LLDPE (Exxon MobileTM LL4004EL) was reacted with different doses of dicumyl peroxide (DCP). The samples were analyzed by size-exclusion chromatography coupled with a light scattering detector. The dynamic shear oscillatory measurements showed a deviation of the δ-׀G ׀٭curve from that of the linear LLDPE, which can be attributed to the presence of long-chain branching (LCB). By the use of a simple rheological method that utilizes melt rheology, transformations in molecular architecture induced on an originally linear low density polyethylene during the early stages of reactive modification were indicated. Reasonable and consistent estimates are obtained, concerning the degree of LCB, the volume fraction of the various molecular species produced in peroxide modification of LLDPE.

Keywords: linear low-density polyethylene, peroxide modification, long-chain branching, rheological method

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Authors: Kariem Elhelow

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The task of optimizing teeth surface relations remains perplexing for many dental practitioners. The well-being of teeth, periodontium, and the musculoskeletal system is closely associated with occlusal stability. Dental occlusion is rather far beyond the simple contact of the occlusal surfaces of the opposite jaws, a fact that turned the word “Occlusion” into one of the most complicated puzzles in dentistry. The literature describing the pathological approaches made the practice of occlusion even more intimidating. Understanding the biomechanics of teeth and jaw movements makes the goals of occlusal rehabilitation very lively and simple to practice. The purpose of this article is to establish a path for understanding and practicing the fundamental occlusal principles in a simple yet in depth way. Relying of the evidence based core would deliver a context for showing that occlusion is not as complicated as literatures might reflect. Conclusion: Maintaining a well-defined picture of what a healthy occlusion should be like is very gratifying to both the operator and the patient, with added worth of predictability, esthetics, and function to the whole treatment.

Keywords: occlusal, temporomandibular joint, prosthetic, dentition

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Simon Espigolé, Igor Shalyminov, Helen Hastie

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Deep machine learning techniques including deep neural networks (DNN) have been used to model language and dialogue for conversational agents to perform tasks, such as giving technical support and also for general chit-chat. They have been shown to be capable of generating long, diverse and coherent sentences in end-to-end dialogue systems and natural language generation. However, these systems tend to imitate the training data and will only generate the concepts and language within the scope of what they have been trained on. This work explores how deep neural networks can be used in a task that would normally require human creativity, whereby the human would read the movie description and/or watch the movie and come up with a compelling, interesting movie title. This task differs from simple summarization in that the movie title may not necessarily be derivable from the content or semantics of the movie description. Here, we train a type of DNN called a sequence-to-sequence model (seq2seq) that takes as input a short textual movie description and some information on e.g. genre of the movie. It then learns to output a movie title. The idea is that the DNN will learn certain techniques and approaches that the human movie titler may deploy that may not be immediately obvious to the human-eye. To give an example of a generated movie title, for the movie synopsis: ‘A hitman concludes his legacy with one more job, only to discover he may be the one getting hit.’; the original, true title is ‘The Driver’ and the one generated by the model is ‘The Masquerade’. A human evaluation was conducted where the DNN output was compared to the true human-generated title, as well as a number of baselines, on three 5-point Likert scales: ‘creativity’, ‘naturalness’ and ‘suitability’. Subjects were also asked which of the two systems they preferred. The scores of the DNN model were comparable to the scores of the human-generated movie title, with means m=3.11, m=3.12, respectively. There is room for improvement in these models as they were rated significantly less ‘natural’ and ‘suitable’ when compared to the human title. In addition, the human-generated title was preferred overall 58% of the time when pitted against the DNN model. These results, however, are encouraging given the comparison with a highly-considered, well-crafted human-generated movie title. Movie titles go through a rigorous process of assessment by experts and focus groups, who have watched the movie. This process is in place due to the large amount of money at stake and the importance of creating an effective title that captures the audiences’ attention. Our work shows progress towards automating this process, which in turn may lead to a better understanding of creativity itself.

Keywords: creativity, deep machine learning, natural language generation, movies

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Authors: Yi-Ling Chen, Dung-Ying Lin

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In the manufacturing process, computer numerical control (CNC) machining plays a crucial role. CNC enables precise machinery control through computer programs, achieving automation in the production process and significantly enhancing production efficiency. However, traditional CNC production lines often require manual intervention for loading and unloading operations, which limits the production line's operational efficiency and production capacity. Additionally, existing CNC automation systems frequently lack sufficient intelligence and fail to achieve optimal configuration efficiency, resulting in the need for substantial time to reconfigure production lines when producing different products, thereby impacting overall production efficiency. Using the NSGA-II algorithm, we generate production line layout configurations that consider field constraints and select robotic arm specifications from an arm list. This allows us to calculate loading and unloading times for each job order, perform demand allocation, and assign processing sequences. The NSGA-II algorithm is further employed to determine the optimal processing sequence, with the aim of minimizing demand completion time and maximizing average machine utilization. These objectives are used to evaluate the performance of each layout, ultimately determining the optimal layout configuration. By employing this method, it enhance the configuration efficiency of CNC production lines and establish an adaptive capability that allows the production line to respond promptly to changes in demand. This will minimize production losses caused by the need to reconfigure the layout, ensuring that the CNC production line can maintain optimal efficiency even when adjustments are required due to fluctuating demands.

Keywords: evolutionary algorithms, multi-objective optimization, pareto optimality, layout optimization, operations sequence

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Authors: Comfort Mokgothu

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This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.

Keywords: decision making, fitness, information processing, reaction time, cognition movement time

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Authors: Reshu Saxena, R. K. Tripathi

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HIV-1 transmission and spread involves significant host-virus interaction. Potential targets for prevention of HIV-1 lies at the site of mucosal barriers. Thus a better understanding of how HIV-1 infects target cells at such sites and lead their invasion is required, with prime focus on the host determinants regulating HIV-1 spread. HIV-1 Nef is important for viral infectivity and pathogenicity. It promotes HIV-1 replication, facilitating immune evasion by interacting with various host factors and altering cellular pathways via multiple protein-protein interactions. In this study nef was sequenced from HIV-1 patients, and showed specific mutations revealing sequence variability in nef. To explore the difference in Nef functionality based on sequence variability we have studied the effects of HIV-1 Nef in human SupT1 T cell line and (THP-1) monocyte-macrophage cell lines through proteomics approach. 2D-Gel Electrophoresis in control and Nef-transfected SupT1 cells demonstrated several differentially expressed proteins with significant modulation of alpha-enolase. Through further studies, effects of Nef on alpha-enolase regulation were found to be cell lineage-specific, being stimulatory in macrophages/monocytes, inhibitory in T cells and without effect in HEK-293 cells. Cell migration and invasion studies were employed to determine biological function affected by Nef mediated regulation of alpha-enolase. Cell invasion was enhanced in THP-1 cells but was inhibited in SupT1 cells by wildtype nef. In addition, the modulation of enolase and cell invasion remained unaffected by a unique nef variant. These results indicated that regulation of alpha-enolase expression and invasive property of host cells by Nef is sequence specific, suggesting involvement of a particular motif of Nef. To precisely determine this site, we designed a heptapeptide including the suggested alpha-enolase regulating sequence of nef and a nef mutant with deletion of this site. Macrophages/monocytes being the major cells affected by HIV-1 at mucosal barriers, were particularly investigated by the nef mutant and peptide. Both the nef mutant and heptapeptide led to inhibition of enhanced enolase expression and increased invasiveness in THP-1 cells. Together, these findings suggest a possible mechanism of host invasion by HIV-1 through Nef mediated regulation of alpha-enolase and identifies a potential therapeutic target for HIV-1 entry at mucosal barriers.

Keywords: HIV-1 Nef, nef variants, host-virus interaction, tissue invasion

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Authors: Rajkumar Ghosh

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The Out-of-Sequence Thrust (OOST) is a common phenomenon in collisional tectonic settings like the Himalayas. These OOSTs are activated in different locations at different time frames. These OOST are linked with the multiple Himalayan Thrusts. Apart from minimal documentation in geological mapping for OOST, there exists a lack of field data to establish OOST in the field. This work has considered three thrusts from NW Himalaya in Himachal Pradesh with published data from other sources, allowing a re-examination for correlation of OOST. For the Sutlej section, the approach has been to do fieldwork and microstructural studies. The information related to the cross-cut signature of S/C- and relative time relation could help to predict the nature of OOST. The activation timing, along with the basis of identification of OOST in Higher Himalayan, was documented in various literature. Compilation of the Grain Boundary Migration (GBM) associated temperature range (400–750 °C) was documented from microstructural studies along the Jhakri-Chaura section. No such significant temperature variation across thrusts was observed. Strain variation paths using S Ʌ C angle measurement were carried out along the Jeori-Wangtu transect to distinguish overprinting structures for OOSTs. Near the Chaura Thrust (CT), angular variation of S Ʌ C was documented, and it varies within a range of 15° - 28 °. Along the NH22 (National Highway, 22), all tectonic units of the orogen are exposed in NW Himalaya, INDIA. But there are inherent difficulties in finding field evidence of OOST, largely due to the lack of adequate surface morphology, including topography and drainage pattern.

Keywords: out-of-sequence thrust (OOST), main central thrust (MCT), south tibetan detachment system (STDS), jhakri thrust (JT), sarahan thrust (ST), chaura thrust (CT), higher himalaya (HH), greater himalayan crystalline (GHC)

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Authors: Shih-Kuei Lin

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The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Ogbe E. E., Ossia. C. V., Saturday. E. G., Ezekwe M. C.

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The disparity in power output between a simple and a modified gas turbine plant is noticeable when the gas turbine functions under local environmental conditions that deviate from the standard ISO specifications. Extensive research and literature have demonstrated a well-known direct correlation between ambient temperature and the power output of a gas turbine plant. In this study, the Omotosho gas turbine plant was modified into three different configurations. The reason for the modification is to improve its performance and reduce the fuel consumption and emission rate. Aspen Hysys software was used to simulate both the simple (Omotosho) and the three modified gas turbine plants. The input parameters considered include ambient temperature, air mass flow rate, fuel mass flow rate, water mass flow rate, turbine inlet temperature, compressor efficiency, and turbine efficiency, while the output parameters considered are thermal efficiency, specific fuel consumption, heat rate, emission rate, compressor power, turbine power and power output. The three modified gas turbine power plants incorporate an inlet air cooling system and a heat recovery steam generator. The variations between the modifications are due to additional components or enhancements alongside the inlet air cooling system and heat recovery steam generator incorporated; the first modification has an additional turbine, the second modification has an additional combustion chamber, and the third modification has an additional turbine and combustion chamber. This paper clearly shows ambient temperature effects on both the simple and three modified gas turbine plants. for every 10-degree kelvin increase in ambient temperature, there is an approximate reduction of 3977 kW, 4795 kW, 4681 kW, and 4793 kW of the power output for the simple gas turbine, first, second, and third modifications, respectively. Also, for every 10-degree kelvin increase in temperature, there is a thermal efficiency decrease of 1.22%, 1.45%, 1.43%, and 1.44% for the simple gas turbine, first, second, and third modifications respectively. Low ambient temperature will help save fuel; looking at the high price of fuel presently in Nigeria for every 10 degrees kelvin increase in temperature, there is a specific fuel consumption increase of 0.0074 kg/kWh, 0.0051 kg/kWh, 0.0061 kg/kWh, and 0.0057 kg/kWh for the simple gas turbine, first, second, and third modifications respectively. These findings will aid in accurately evaluating local power generating plants, particularly in hotter regions, for installing gas turbine inlet air cooling (GTIAC) systems.

Keywords: Aspen HYSYS software, Brayton Cycle, modified gas turbine, power plant, simple gas turbine, thermal efficiency.

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: Lynette Lincoln, Sunil S. More

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With the rising demand of sugar used today, it is proposed that world sugar is expected to escalate up to 203 million tonnes by 2021. Hydrolysis of sucrose (table sugar) into glucose and fructose equimolar mixture is catalyzed by β-D-fructofuranoside fructohydrolase (EC 3.2.1.26), commonly called as invertase. For fluid filled center in chocolates, preparation of artificial honey, as a sweetener and especially to ensure that food stuffs remain fresh, moist and soft for longer spans invertase is applied widely and is extensively being used. From an industrial perspective, properties such as increased solubility, osmotic pressure and prevention of crystallization of sugar in food products are highly desired. Screening for invertase does not involve plate assay/qualitative test to determine the enzyme production. In this study, we use a three-step screening strategy for identification of a novel bacterial isolate from soil which is positive for invertase production. The primary step was serial dilution of soil collected from sugarcane fields (black soil, Maddur region of Mandya district, Karnataka, India) was grown on a Czapek-Dox medium (pH 5.0) containing sucrose as the sole C-source. Only colonies with the capability to utilize/breakdown sucrose exhibited growth. Bacterial isolates released invertase in order to take up sucrose, splitting the disaccharide into simple sugars. Secondly, invertase activity was determined from cell free extract by measuring the glucose released in the medium at 540 nm. Morphological observation of the most potent bacteria was examined by several identification tests using Bergey’s manual, which enabled us to know the genus of the isolate to be Bacillus. Furthermore, this potent bacterial colony was subjected to 16S rDNA PCR amplification and a single discrete PCR amplicon band of 1500 bp was observed. The 16S rDNA sequence was used to carry out BLAST alignment search tool of NCBI Genbank database to obtain maximum identity score of sequence. Molecular sequencing and identification was performed by Xcelris Labs Ltd. (Ahmedabad, India). The colony was identified as Bacillus sp. BAB-3434, indicating to be the first novel strain for extracellular invertase production. Molasses, a by-product of the sugarcane industry is a dark viscous liquid obtained upon crystallization of sugar. An enhanced invertase production and optimization studies were carried out by one-factor-at-a-time approach. Crucial parameters such as time course (24 h), pH (6.0), temperature (45 °C), inoculum size (2% v/v), N-source (yeast extract, 0.2% w/v) and C-source (molasses, 4% v/v) were found to be optimum demonstrating an increased yield. The findings of this study reveal a simple screening method of an extracellular invertase from a rapidly growing Bacillus sp., and selection of best factors that elevate enzyme activity especially utilization of molasses which served as an ideal substrate and also as C-source, results in a cost-effective production under submerged conditions. The invert mixture could be a replacement for table sugar which is an economic advantage and reduce the tedious work of sugar growers. On-going studies involve purification of extracellular invertase and determination of transfructosylating activity as at high concentration of sucrose, invertase produces fructooligosaccharides (FOS) which possesses probiotic properties.

Keywords: Bacillus sp., invertase, molasses, screening, submerged fermentation

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Authors: Sweta Pandey, Samridhi Dhyani, Susmita Chaudhuri

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Klebsiella pneumoniae bacteria is a global threat to human health due to an increase in multi-drug resistance among strains. The hypervirulent strains of Klebsiella pneumoniae is a major trouble due to their association with life-threatening infections in a healthy population. One of the major virulence factors of hyper virulent strains of Klebsiella pneumoniae is the T6SS (Type six secretary system) which is majorly involved in microbial antagonism and causes interaction with the host eukaryotic cells during infections. T6SS mediates some of the crucial factors for establishing infection by the bacteria, such as cell adherence, invasion, and subsequent in vivo colonisation. The antibacterial activity and the cell invasion property of the T6SS system is a major requirement for the establishment of K. pneumoniae infections within the gut. The T6SS can be an appropriate target for developing therapeutics. The T6SS consists of an inner tube comprising hexamers of Hcp (Haemolysin -regulated protein) protein, and at the top of this tube sits VgrG (Valine glycine repeat protein G); the tip of the machinery consists of PAAR domain containing proteins which act as a delivery system for bacterial effectors. For this study, immune response to recombinant VgrG protein was generated to establish this protein as a potential immunogen for the development of therapeutic leads. The immunogenicity of the selected protein was determined by predicting the B cell epitopes by the BCEP analysis tool. The gene sequence for multiple domains of VgrG protein (phage_base_V, T6SS_Vgr, DUF2345) was selected and cloned in pMAL vector in E. coli. The construct was subcloned and expressed as a fusion protein of 203 residue protein with mannose binding protein tag (MBP) to enhance solubility and purification of this protein. The purified recombinant VgrG fusion protein was used for mice immunisation. The antiserum showed reactivity with the recombinant VgrG in ELISA and western blot. The immunised mice were challenged with K. pneumoniae bacteria and showed bacterial clearance in immunised mice. The recombinant VgrG protein can further be used for studying downstream signalling of VgrG protein in mice during infection and for therapeutic MAb development to eradicate K. pneumoniae infections.

Keywords: immune response, Klebsiella pneumoniae, multi-drug resistance, recombinant protein expression, T6SS, VgrG

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Authors: G. Sava, I. Popa, T. Sava, A. Ion, M. Ilie, C. Manailescu, A. Robu

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At the RoAMS laboratory in Bucharest we have looked for a head-to-head meeting between AMS radiocarbon dating and dendrochronology dating, aiming to point out and explain any differences or similarities that might appear between their output results. As a subject of this investigation, we have fixed our attention on a sequence of tree rings spanning on a period of 700 years, starting with 1000 AD. The samples were collected from the northern Romanian territory within Moldavia region, and were provided by the ‘Marin Dracea - National Institute for Research and Development in Forestry’. All the 23 single ring wood samples were radiocarbon dated using alpha-cellulose extraction, followed by graphitization in an AGE3 installation. A wiggle matching procedure was applied to reduce the radiocarbon uncertainties for the calibrated ages. The results showed a good agreement on 3 out of 4 wood cores, the age-shifting of one of the wood cores being interpreted as an uncertain dendrochronology matching, which was further corrected.

Keywords: wiggle matching, tree-ring radiocarbon dating, dendrochronology, AMS radiocarbon dating, radiocarbon dating in Romania

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Authors: Elena Pozdnyakova

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“Government Relations” is a field of knowledge presently taught at the majority of universities around the globe. English as the default language can become the language of teaching since the issues discussed are both global and national in character. However for this field of knowledge key concepts and their word representations in English don’t often coincide with those in other languages. International master’s degree students abroad as well as students, taught the course in English at their national universities, are exposed to difficulties, connected with correct conceptualizing of terminology of GR in British and American academic traditions. The study was carried out during the GR English language course elaboration (pilot research: 2013 -2015) at Moscow State Institute of Foreign Relations (University), Russian Federation. Within this period, English language instructors designed and elaborated the three-semester course of GR. Methodologically the course design was based on elaboration model with the special focus on conceptual elaboration sequence and theoretical elaboration sequence. The course designers faced difficulties in concept selection and theoretical elaboration sequence. To improve the results and eliminate the problems with concept selection, a new, corpus-based approach was worked out. The computer-based tool WordSmith 6.0 was used with the aim to build a model of key concept selection. The corpus of GR English texts consisted of 1 million words (the study corpus). The approach was based on measuring effect size, i.e. the percent difference of the frequency of a word in the study corpus when compared to that in the reference corpus. The results obtained proved significant improvement in the process of concept selection. The corpus-based model also facilitated theoretical elaboration of teaching materials.

Keywords: corpus-based study, English as the default language, key concepts, measuring effect size, model of key concept selection

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Authors: P. K. Telengech, K. Monjero, J. Maling’a, A. Nyende, S. Gichuki

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There is need to identify an efficient protocol for use in extraction of high quality DNA for purposes of molecular work. Cassava roots are known for their high starch content, polyphenols and other secondary metabolites which interfere with the quality of the DNA. These factors have negative interference on the various methodologies for DNA extraction. There is need to develop a simple, fast and inexpensive protocol that yields high quality DNA. In this improved Dellaporta method, the storage roots are lyophilized to reduce the water content; the extraction buffer is modified to eliminate the high polyphenols, starch and wax. This simple protocol was compared to other protocols intended for plants with similar secondary metabolites. The method gave high yield (300-950ng) and pure DNA for use in PCR analysis. This improved Dellaporta protocol allows isolation of pure DNA from starchy cassava storage roots.

Keywords: cassava storage roots, dellaporta, DNA extraction, lyophilisation, polyphenols secondary metabolites

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Authors: Abid Boudiar

Abstract:

We propose a simple model to obtain an exact expression of Tc/(Tc,max) for the temperature-doping phase diagram of superconducting cuprates. We showed that our model predicted most phase diagram scenario. We found the exact special doping points p(opt), p(qcp) and an accurate E(g,max). Some other properties such as the stripes length 100.1°A and the energy gap in cuprates chain
6meV can also be calculated exactly. Another interesting consequence of this simple picture is the new magic numbers and the ability to express everything using a (Tc,p) diagram via the golden ratio.

Keywords: superconducting cuprates, phase, pseudogap, hole doping, strips, golden ratio, soliton

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Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

Abstract:

Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

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Authors: A. Abbasi Moshaii, M. Soltan Rezaee, M. Mohammadi Moghaddam

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Control of some mechanisms is hard because of their complex dynamic equations. If part of the complexity is resulting from uncertainties, an efficient way for solving that is robust control. By this way, the control procedure could be simple and fast and finally, a simple controller can be designed. One kind of these mechanisms is 3-RRR which is a parallel mechanism and has three revolute joints. This paper aims to robust control a 3-RRR planner mechanism and it presents that this could be used for other mechanisms. So, a significant problem in mechanisms control could be solved. The relevant diagrams are drawn and they show the correctness of control process.

Keywords: 3-RRR, dynamic equations, mechanisms control, structural uncertainty

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Authors: Peng Wang, Tigang Jiang

Abstract:

The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

Procedia PDF Downloads 128