Search results for: real number sequences

Authors: Paula Verdugo-Hernandez, Patricio Cumsille

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We analyze a first-class on the convergence of real number sequences, named hereafter sequences, to foster exploration and discovery of concepts through graphical representations before engaging students in proving. The main goal was to differentiate between sequences and continuous functions-of-a-real-variable and better understand concepts at an initial stage. We applied the analytic frame of mathematical working spaces, which we expect to contribute to extending to sequences since, as far as we know, it has only developed for other objects, and which is relevant to analyze how mathematical work is built systematically by connecting the epistemological and cognitive perspectives, and involving the semiotic, instrumental, and discursive dimensions.

Keywords: convergence, graphical representations, mathematical working spaces, paradigms of real analysis, real number sequences

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Authors: J. Trarbach, S. Schosser, B. Vogt

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Decision-makers tend to prefer the first alternative over subsequent alternatives which is called the primacy effect. To reliably measure this effect, we conducted an experiment with real consequences for preference statements. Therefore, we elicit preferences of subjects using a rating scale, i.e. hypothetical preferences, and willingness to pay, i.e. real preferences, for two sequences of pain. Within these sequences, both overall intensity and duration of pain are identical. Hence, a rational decision-maker should be indifferent, whereas the primacy effect predicts a stronger preference for the first sequence. What we see is a primacy effect only for hypothetical preferences. This effect vanishes for real preferences.

Keywords: decision making, primacy effect, real incentives, willingness to pay

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Authors: Yaw-Ling Lin

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A de Bruijn graph of order k is a graph whose vertices representing all length-k sequences with edges joining pairs of vertices whose sequences have maximum possible overlap (length k−1). Every Hamiltonian cycle of this graph defines a distinct, minimum length de Bruijn sequence containing all k-mers exactly once. A Kautz sequence is the minimal generating sequence so as the sequence of minimal length that produces all possible length-k sequences with the restriction that every two consecutive alphabets in the sequences must be different. A collection of de Bruijn/Kautz sequences are orthogonal if any two sequences are of maximally differ in sequence composition; that is, the maximum length of their common substring is k. In this paper, we discuss how such a collection of (maximal) orthogonal de Bruijn/Kautz sequences can be made and use the algorithm to build up a web application service for the synthesized DNA and other related biomolecular sequences.

Keywords: biomolecular sequence synthesis, de Bruijn sequences, Eulerian cycle, Hamiltonian cycle, Kautz sequences, orthogonal sequences

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

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

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

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Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Bilal Wajid, Erchin Serpedin

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The health industry is aiming towards personalized medicine. If the patient’s genome needs to be sequenced it is important that the entire analysis be completed quickly. This paper explores use of parallel computing to analyze very large sequences. Two cases have been considered. In the first case, the sequence is kept constant and the effect of increasing the number of MPI-based processes is evaluated in terms of execution time, speed and efficiency. In the second case the number of MPI-based processes have been kept constant whereas, the length of the sequence was increased.

Keywords: parallel computing, alignment, genome assembly, alignment

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Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: Ric Joseph R. Murillo, Edna N. Gueco, Dennis I. Merino

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Let F be C or R, where C and R are the set of complex numbers and real numbers, respectively, and n be a natural number. An n-by-n matrix A over the field F is called an α-involutory matrix or an α-involution if there exists an α in the field such that the square of the matrix is equal to αI, where I is the n-by-n identity matrix. If α is a complex number or a nonnegative real number, then an n-by-n matrix A over the field F can be written as a sum of n-by-n α-involutory matrices over the field F if and only if the trace of that matrix is an integral multiple of the square root of α. Meanwhile, if α is a negative real number, then a 2n-by-2n matrix A over R can be written as a sum of 2n-by-2n α-involutory matrices over R if and only the trace of the matrix is zero. Some other properties of α-involutory matrices are also determined

Keywords: α-involutory Matrices, sum of α-involutory Matrices, Trace, Matrix Theory

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Authors: Noshaba Dilbar, Aisha Tahir, Amer Jamil

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During the last decade, DNA barcoding proved to be an authentic tool for discovery and identification of plants. In the present study, DNA barcoding of two species, Fagonia arabica and Fagonia indica was done for differentiation by using matK region. matK gene is considered as a universal barcode because of its easy alignment and high discrimination ability. In this study, matK yielded 100% sequencing results. The sequences from both plants were aligned at clustal W and observed that there is no nucleotide variation and polymorphism among both sequences. This was further analysed by BLAST which showed the similar sequences from different plants belonging to same family but didn’t find sequence of both species. Considering this, the resulted sequence was submitted by the name of Fagonia arabica with accession number KM276890. In the end, we analysed the results from BOLD which gave us the final conclusion that both plants are same as their matK sequences are 100% identical. In literature, both Fagonia indica and Fagonia arabica names are used for this plant but there is no clear differentiation has been observed in these plants. Results evaluate that Fagonia indica and Fagonia arabica are the alternative names of same plant.

Keywords: DNA barcoding, Fagonia arabica, Fagonia indica, matK

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Authors: Salem Ben Said

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In recent times the decimal number system to which we are accustomed has received serious competition from the binary number system. In this note, an approach is suggested to teaching and learning the binary number system using examples from the real world. More precisely, we will demonstrate the utility of the binary system in describing the optimal strategy to win the Chinese Nim game, and in telegraphy by decoding the hidden message on Perseverance’s Mars parachute written in the language of binary system. Finally, we will answer the question, “why do modern computers prefer the ternary number system instead of the binary system?”. All materials are provided in a format that is conductive to classroom presentation and discussion.

Keywords: binary number system, Nim game, telegraphy, computers prefer the ternary system

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Authors: Letizia Maria Drammis, Maria Antonella Brandimonte

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The idea that people use space representations to think about time and number received support from several lines of research. However, how these representations develop in children and then shape space-time and space-number mappings is still a debated issue. In the present study, 40 children (20 pre-schoolers and 20 elementary-school children) performed 4 main tasks, which required the use of more concrete (non-symbolic) or more abstract (symbolic) space-time and space-number associations. In the non-symbolic conditions, children were required to order pictures of everyday-life events occurring in a specific temporal order (Temporal sequences) and of quantities varying in numerosity (Numerical sequences). In the symbolic conditions, they were asked to perform the typical time-to-position and number-to-position tasks by mapping time-related words and numbers onto lines. Results showed that children performed reliably better in the non-symbolic Time conditions than the symbolic Time conditions, independently of age, whereas only pre-schoolers performed worse in the Number-to-position task (symbolic) as compared to the Numerical sequence (non-symbolic) task. In addition, only older children mapped time-related words onto space following the typical left-right orientation, pre-schoolers’ performance being somewhat mixed. In contrast, mapping numbers onto space showed a clear left-right orientation, independently of age. Overall, these results indicate a cross-domain difference in the way younger and older children process time and number, with time-related tasks being more difficult than number-related tasks only when space-time tasks require symbolic representations.

Keywords: space-time associations, space-number associations, orientation, children

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Fadime Eroglu

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Acanthamoeba genus belongs to kingdom protozoa, and it is known as free-living amoebae. Acanthamoeba genus has been isolated from human bodies, swimming pools, bottled mineral water, contact lens solutions, dust, and soil. The members of the genus Acanthamoeba causes Acanthamoeba Keratitis which is a painful sight-threatening disease of the eyes. In recent years, the prevalence of Acanthamoeba keratitis has been high rate reported. The eight different Acanthamoeba species are known to be effective in Acanthamoeba keratitis. These species are Acanthamoeba castellanii, Acanthamoeba polyphaga, Acanthamoeba griffini, Acanthamoeba hatchetti, Acanthamoeba culbertsoni and Acanhtamoeba rhysodes. The conventional diagnosis of Acanthamoeba Keratitis has relied on cytological preparations and growth of Acanthamoeba in culture. However molecular methods such as real-time PCR has been found to be more sensitive. The real-time PCR has now emerged as an effective method for more rapid testing for the diagnosis of infectious disease in decade. Therefore, a real-time PCR assay for the detection of Acanthamoeba keratitis and Acanthamoeba species have been developed in this study. The 18S rRNA sequences from Acanthamoeba species were obtained from National Center for Biotechnology Information and sequences were aligned with MEGA 6 programme. Primers and probe were designed using Custom Primers-OligoPerfectTMDesigner (ThermoFisherScientific, Waltham, MA, USA). They were also assayed for hairpin formation and degree of primer-dimer formation with Multiple Primer Analyzer ( ThermoFisherScientific, Watham, MA, USA). The eight different ATCC Acanthamoeba species were obtained, and DNA was extracted using the Qiagen Mini DNA extraction kit (Qiagen, Hilden, Germany). The DNA of Acanthamoeba species were analyzed using newly designed primer and probe set in real-time PCR assay. The early definitive laboratory diagnosis of Acanthamoeba Keratitis and the rapid initiation of suitable therapy is necessary for clinical prognosis. The results of the study have been showed that new primer and probes could be used for detection and distinguish for Acanthamoeba species. These new developing methods are helpful for diagnosis of Acanthamoeba Keratitis.

Keywords: Acathamoeba Keratitis, Acanthamoeba species, fast diagnosis, Real-Time PCR

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Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Osaretin Rosemary Uyi, A. O. Ogungbemi

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Female involvement in policy making and partnership in a man-driven-world is fast gaining international recognition. The Nigeria commercial real estate is one of the sectors of the economy that has a significant number of the male in the business. This study was conducted to assess the participation of females in estate management in Lagos state, Nigeria. Lagos is the commercial nerve center of Nigeria having the highest number of real estate practitioners and investors. The population due to the daily influx of people has made real estate business to continue to grow in this part of Nigeria. A structured questionnaire duly pre-tested and validated was used to elicit information from the respondents. The data collected were presented using tables and charts and were analyzed using descriptive statistical tools such as frequency counts, percentages, were used to test the hypothesis. The results also indicated that most females that participated in commercial real estate business are educated (80%), fell within 31-40 years of age (75%) and of high income status (88%) earn above ₦800,000 per year, while 10% are real estate investors and 82% of the female in the sector are employee. The study concluded that the number of female participating in various aspect of commercial real estate business in the study area was moderate while the numbers of female investors are low when compared to male. This might be due to the problems associated with rent collection, land disputes and other issues that are associated with property management in Nigeria. It is therefore recommended that females in real estate should be empowered and encouraged to match with their male counterpart.

Keywords: commercial real estate, empowerment, female, participation, property management

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Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

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A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: bacteria chromosome, bacterial identification, sequence, primer generation

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: T. Padma, Jayashree S. Pillai

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Random entities are an essential component in any cryptographic application. The suitability of a number theory based novel pseudorandom sequence called Pseudorandom Partial Quotient Sequence (PPQS) generated from the continued fraction expansion of irrational numbers, in cryptographic applications, is analyzed in this paper. An approach to build the algorithm around a hard mathematical problem has been considered. The PQ sequence is tested for randomness and its suitability as a cryptographic key by performing randomness analysis, key sensitivity and key space analysis, precision analysis and evaluating the correlation properties is established.

Keywords: pseudorandom sequences, key sensitivity, correlation, security analysis, randomness analysis, sensitivity analysis

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Authors: F. Berna Benli, Özgür Keskin

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Lately, many mathematicians have been studied the statistical convergence of a sequence of fuzzy numbers. We know that Lambda-statistically convergence is a kind of convergence between ordinary convergence and statistical convergence. In this paper, we will introduce the new kind of convergence such as λ-levelwise statistical convergence. Then, we will define the concept of the λ-levelwise statistical cluster and limit points of a sequence of fuzzy numbers. Also, we will discuss the relations between the sets of λ-levelwise statistical cluster points and λ-levelwise statistical limit points of sequences of fuzzy numbers. This work has been extended in this paper, where some relations have been considered such that when lambda-statistical limit inferior and lambda-statistical limit superior for lambda-statistically convergent sequences of fuzzy numbers are equal. Furthermore, lambda-statistical boundedness condition for different sequences of fuzzy numbers has been studied.

Keywords: fuzzy number, λ-levelwise statistical cluster points, λ-levelwise statistical convergence, λ-levelwise statistical limit points, λ-statistical cluster points, λ-statistical convergence, λ-statistical limit points

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Authors: Yuhei Kunihiro, Sorin V. Sabau, Kazuhiro Shibuya

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We study the molecular evolution of insulin from the metric geometry point of view. In mathematics, and particularly in geometry, distances and metrics between objects are of fundamental importance. Using a weaker notion than the classical distance, namely the weighted quasi-metrics, one can study the geometry of biological sequences (DNA, mRNA, or proteins) space. We analyze from the geometrical point of view a family of 60 insulin homologous sequences ranging on a large variety of living organisms from human to the nematode C. elegans. We show that the distances between sequences provide important information about the evolution and function of insulin.

Keywords: metric geometry, evolution, insulin, C. elegans

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Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu

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Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.

Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Sabeen Alam, Mehboob Alam

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The research work entitled “Effect of Bacillus pumilus strains on heavy metal accumulation in lettuce grown on contaminated soil” focused on functional role of Bacillus pumilus strains inoculated with lettuce seed in mitigating heavy metal in chromite mining soil. In this experiment, factor A was three Bacillus pumilus strains (sequence C-2PMW-8, C-1 SSK-8 and C-1 PWK-7) while soil used for this experiment was collected from Prang Ghar mining site and lettuce seeds were grown in three levels of chromite mining soil (2.27, 4.65 and 7.14 %). For mining soil minimum days to germinate noted in lettuce grown on garden soil inoculated with sequence. Maximum germination percentage noted was for C-1 SSK-8 grown on garden soil, maximum lettuce height for sequence C-2 PWM-8, fresh leaf weight for C-1 PWK-7 inoculated lettuce, dry weight of lettuce leaf for lettuce inoculated with C-1 SSK-8 and C-1 PWK-7 strains, number of leaves per plant for lettuce inoculated with C-1 SSK-8, leaf area for C-2 PMW-8 inoculated lettuce, survival percentage for C-1 SSK-8 treated lettuce and chlorophyll content for C-2 PMW-8. Results related to heavy metals accumulation showed that minimum chromium was in lettuce and in soil for all three sequences, cadmium (Cd) in lettuce and in soil for all three sequences, manganese (Mn) in lettuce and in soil for three sequences, lead (Pb) in lettuce and in soil for three sequences. It can be concluded that chromite mining soil significantly reduced the growth and survival of lettuce, but when lettuce was inoculated with Bacillus.pumilus strains, it enhances growth and survival. Similarly, minimum heavy metal accumulation in plant and soil, regardless of type of Bacillus pumilus used, all three sequences has same mitigating effect on heavy metal in both soil and lettuce. All the three Bacillus pumilus strains ensured reduction in heavy metals content (Mn, Cd, Cr) in lettuce, below the maximum permissible limits of WHO 2011.

Keywords: bacillus pumilus, heavy metals, permissible limits, lettuce, chromite mining soil, mitigating effect

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Authors: Jeongyeob Hong, Myeonghoon Park, Taeson Yoon

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After the advent of Achaeans which utilize different metabolism pathway and contain conspicuously different cellular structure, they have been recognized as possible materials for developing quality of human beings. Among diverse Achaeans, in this paper, we compared 16s RNA Sequences of four different species of Thermococcus: Achaeans genus specialized in sulfur-dealing metabolism. Four Species, Barophilus, Kodakarensis, Hydrothermalis, and Onnurineus, live near the hydrothermal vent that emits extreme amount of sulfur and heat. By comparing ribosomal sequences of aforementioned four species, we found similarities in their sequences and expressed protein, enabling us to expect that certain ribosomal sequence or proteins are vital for their survival. Apriori algorithms and Decision Tree were used. for comparison.

Keywords: Achaeans, Thermococcus, apriori algorithm, decision tree

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Authors: Denis Obrul, Borut Žalik

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We present an extendable online real-time tracking platform that can be used to track a wide variety of location-aware devices. These can range from GPS devices mounted inside a vehicle, closed and secure systems such as Teltonika and to mobile phones running multiple platforms. Special consideration is given to decentralized approach, security and flexibility. A number of different use cases are presented as a proof of concept.

Keywords: real-time, online, gps, tracking, web application

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Authors: Yingxu Wang

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This work presents basic research on the recursive structures and dual sequential patterns of primes for the formal proof of the Twin-Prime Conjecture (TPC). A rigorous methodology of Twin-Prime Decomposition (TPD) is developed in MATLAB to inductively verify potential twins in the dual sequences of primes. The key finding of this basic study confirms that the dual sequences of twin primes are not only symmetric but also infinitive in the unique base 6 cycle, except a limited subset of potential pairs is eliminated by the lack of dual primality. Both theory and experiments have formally proven that the infinity of twin primes stated in TPC holds in the P x P space.

Keywords: number theory, primes, twin-prime conjecture, dual primes (P x P), twin prime decomposition, formal proof, algorithm

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Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Ghazanfar Ali, Fahad N Almajhdi

Abstract:

This study provides data on the viral diagnosis and molecular epidemiology of influenza A(H3N2) virus isolated in Riyadh, Saudi Arabia. Nasopharyngeal aspirates from 80 clinically infected patients in the peak of the 2010-2011 winter seasons were processed for viral diagnosis by RT-PCR. Sequencing of entire HA and NA genes of representative isolates and molecular epidemiological analysis were performed. A total of 06 patients were positive for influenza A, B and respiratory syncytial viruses by RT-PCR assays; out of these only one sample was positive for influenza A(H3N2) by RT-PCR. Phylogenetic analysis of the HA and NA gene sequences showed identities higher than 99-98.8 % in both genes. They were also similar to reference isolates in HA sequences (99 % identity) and in NA sequences (99 % identity). Amino acid sequences predicted for the HA gene were highly identical to reference strains. The NA amino acid substitutions identified did not include the oseltamivir-resistant H275Y substitution. Conclusion: Viral isolation and RT-PCR together were useful for diagnosis of the influenza A (H3N2) virus. Variations in HA and NA sequences are similar to those identified in worldwide reference isolates and no drug resistance was found.

Keywords: influenza A (H3N2), genetic characterization, viral isolation, RT-PCR, Saudi Arabia

Procedia PDF Downloads 233