Search results for: bioinformatics pipeline

Authors: Atef Ibrahim, Hamed Elsimary, Abdullah Aljumah, Fayez Gebali

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This paper presents a novel semi-systolic array architecture for an optimized parallel sequence alignment algorithm. This architecture has the advantage that it can be modified to be reused for multiple pass processing in order to increase the number of processing elements that can be packed into a single FPGA and to increase the number of sequences that can be aligned in parallel in a single FPGA. This resolves the potential problem of many FPGA resources left unused for designs that have large values of short read length. When using the previously published conventional hardware design. FPGA implementation results show that, for large values of short read lengths (M>128), the proposed design has a slightly higher speed up and FPGA utilization over the the conventional one.

Keywords: bioinformatics, genome sequence alignment, re-sequencing applications, systolic array

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Authors: Muhammad Arsalan Khan Sherwani

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The use of Volatile Corrosion Inhibitors (VCI) to protect Aboveground Storage Tank (AST) bottom plates against soil-side corrosion is one of the emerging corrosion prevention methods, specifically for tanks constructed on oily sand pad. Oily sand pad and the presence of air gaps underneath the bottom plates lead to severe corrosion and high metal thickness loss. In such cases, the cathodic protection cannot be fully considered as effective due to Cathodic Protection (CP) current shielding. These situations sometimes result in serious failures on multiple fronts, such as; containment losses, system shutdowns, extensive repairs, environmental impact and safety concerns in case of flammable fluids. Recently, East West Pipeline Department (EWPD) of Saudi Aramco has deployed this technology to one of the crude oil storage tanks, which showed high metal thickness loss during its out of service inspection. Soil-side corrosion rustled in major repairs of bottom plates and ultimately caused enormous unplanned activities in term of time as well as cost. This paper mainly focuses on the methodology of VCI installation, corrosion monitoring system and the expected results of protection.

Keywords: Vapor Corrosion Inhibitor, Soil Side Corrosion, External Corrosion, Above Grade Storage Tank

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Authors: Fan Gao, Lior Pachter

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The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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Authors: Sandy Black, Calum McLaughlin, Alessandro Pranzitelli, Marc Laing

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Multiphase flow structures of two-phase multicomponent fluids were experimentally investigated in a large diameter high-pressure pipeline up to 130 bar at TÜV SÜD’s National Engineering Laboratory Advanced Multiphase Facility. One of the main objectives of the experimental test campaign was to evaluate the impact of pressure on multiphase flow patterns as much of the existing information is based on low-pressure measurements. The experiments were performed in a horizontal and vertical orientation in both 4-inch and 6-inch pipework using nitrogen, ExxsolTM D140 oil, and a 6% aqueous solution of NaCl at incremental pressures from 10 bar to 130 bar. To visualise the detailed structure of the flow of the entire cross-section of the pipe, a fast response X-ray tomography system was used. A wide range of superficial velocities from 0.6 m/s to 24.0 m/s for gas and 0.04 m/s and 6.48 m/s for liquid was examined to evaluate different flow regimes. The results illustrated the suppression of instabilities between the gas and the liquid at the measurement location and that intermittent or slug flow was observed less frequently as the pressure was increased. CFD modellings of low and high-pressure simulations were able to successfully predict the likelihood of intermittent flow; however, further tuning is necessary to predict the slugging frequency. The dataset generated is unique as limited datasets exist above 100 bar and is of considerable value to multiphase flow specialists and numerical modellers.

Keywords: computational fluid dynamics, high pressure, multiphase, X-ray tomography

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Authors: Duc Dong Do, Ngoc Ha Tran, Thanh Hai Dang, Cao Cuong Dang, Xuan Huan Hoang

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Global aligning two protein-protein interaction networks is an essentially important task in bioinformatics/computational biology field of study. It is a challenging and widely studied research topic in recent years. Accurately aligned networks allow us to identify functional modules of proteins and/ororthologous proteins from which unknown functions of a protein can be inferred. We here introduce a novel efficient heuristic global network alignment algorithm called FASTAn, including two phases: the first to construct an initial alignment and the second to improve such alignment by exerting a local optimization repeated procedure. The experimental results demonstrated that FASTAn outperformed the state-of-the-art global network alignment algorithm namely SPINAL in terms of both commonly used objective scores and the run-time.

Keywords: FASTAn, Heuristic algorithm, biological network alignment, protein-protein interaction networks

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Authors: Asif Mahmood, Shama Shama, Hao Ni, Hao Wang, Yu Ling, Hui Xu, Shixing Yang, Qais Ahmad Naseer, Wen Zhang

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Cardiovirus is a genus of viruses belonging to the family Picornaviridae. Here, we used viral metagenomic techniques to detect the viral nucleic acid in the fecal samples from wild rats in Zhenjiang city in China. Fecal samples were collected from 20 wild rats and pooled into four sample pools and then subjected to libraries construction which were then sequenced on Illumina MiSeq platform. The sequenced reads were analyzed using viral metagenomic analysis pipeline. A novel cardiovirus from feces of a wild rat was identified, named amzj-2018, of which the complete genome was acquired. Phylogenetic analysis based on the complete amino acid sequence of polyprotein revealed that amzj-2018 formed a separate branch located between clusters of Saffold virus and Rat Theilovirus 1 (RTV-1). Phylogenetic analysis based on different regions of the polyproteins, including P1, P2, P3, and P2+P3, respectively, showed discordant trees, where the tree based on P3 region indicated that amzj-2018 clustered separately between Theiler's murine encephalomyelitis virus and RTV-1. The complete genome of a cardiovirus was determined from the feces of wild rats which belonged to a novel type of cardiovirus based on phylogenetic analysis. Whether it is associated with disease needs further investigation.

Keywords: cardiovirus, viral metagenomics, genomic organization, phylogenetic analysis

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Authors: Setenay Nil Doğan, Ece Oztan

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Research and development (R&D) as a term denotes the innovative studies conducted systematically to increase knowledge and its practices. As R&D intensity of Turkey (0,84%) is quite below the EU average intensity score, it has displayed a continuous increase since the 2000s. Also, the development of human capital in R&D has been one of the basic aims of National Strategy of Science, Technology, and Innovation, and National Innovation System 2023 of Turkey. R&D is considered to one of the fields in which the gender gap is wide. The reflections of the analogy of leaky pipeline, a term used for vertical differentiation in academy can also be observed in those scientific activities related with the private sector. In the private sector, the gender gap becomes wider: the percentage of female researchers in the universities (41%) decreases to 24% in the private sector. Though half of the undergraduates and gradutes are female in Turkey, a widening gender gap is observed in terms of employment in R&D. Given this background, this paper will focus on gendered dynamics of careers in R&D through the interviews conducted with 25 female and 25 male employees, working in a university technopark and some of the large RD centers in Turkey working in several sectors such as electronics, automotive etc. Focusing on some aspects of gender differences in terms of career experiences in R&D and innovation, mobility, participation to the projects, patents and inclusion to other innovatory activities, home-work balance, it aims to explore the relationships between science, technology, innovation and gender.

Keywords: gender, innovation, R&D, science, technology

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Ankan Roy, Niharika, Samir Kumar Patra

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Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.

Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions

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Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

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Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

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Authors: Cheng Fang Hsu

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Call center is the core of building customer relationship management system. Under the strong competitive stress, it becomes a new profiting challenge for a successful enterprise. Call center is a department not only to provide customer service but also to bring business profit. This is the qualitative case study in Taiwan bank service industry which goes on deeper exploration, and analysis by business interviews and industrial analysis. This study starts from the establishment, development, and management after the reforming of the case call center. Through SWOT analysis, and industrial analysis, this study adopted 7S model to explain how the call center reforms from service oriented to profit oriented and from cost management to profit management. The results indicated how service innovation management promotes call center to be operated as a market profit competition center. The recommendations are indicated to support the call center on marketing profit by service innovation management.

Keywords: call center, 7S model, service innovation management, bioinformatics

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Authors: Essam Al Daoud

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Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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Authors: Ahmad S. Mohd Noor, Emma A. Sirajudin, Nur F. Mat Zain

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Reliability is an important property for knowledge repository system. National Marine Bioinformatics System or NABTICS is a marine knowledge repository portal aimed to provide a baseline for marine biodiversity and a tool for researchers and developers. It is intended to be a large and growing online database and also a metadata system for inputs of research analysis. The trends of present large distributed systems such as Cloud computing are the delivery of computing as a service rather than a product. The goal of this research is to make NABTICS a system of greater availability by integrating it with Cloud based Neighbor Replication and Failure Recovery (NRFR). This can be achieved by implementation of NABTICS into distributed environment. As a result, the user can experience minimum downtime while using the system should the server is having a failure. Consequently the online database application is said to be highly available.

Keywords: cloud, availability, distributed system, marine repository, database replication

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Authors: Sirous Eydivandi

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Diacylglycerol-O-acyltransferase (DGAT1) gene encodes diacylglycerol transferase enzyme that plays an important role in glycerol lipid metabolism. DGAT1 is considered to be the key enzyme in controlling the synthesis of triglycerides in adipocytes. This enzyme catalyzes the final step of triglyceride synthesis (transform triacylglycerol (DAG) into triacylglycerol (TAG). A total of 20 DGAT1 gene sequences and corresponding amino acids belonging to 4 species include cattle, goats, sheep and yaks were analyzed, and the differentiation within and among the species was also studied. The length of the DGAT1 gene varies greatly, from 1527 to 1785 bp, due to deletion, insertion, and stop codon mutation resulting in elongation. Observed genetic diversity was higher among species than within species, and Goat had more polymorphisms than any other species. Novel amino acid variation sites were detected within several species which might be used to illustrate the functional variation. Differentiation of the DGAT1 gene was obvious among species, and the clustering result was consistent with the taxonomy in the National Center for Biotechnology Information.

Keywords: DGAT1gene, bioinformatic, ruminnants, biotechnology information

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Authors: Rosa Buxeda, Lorenzo Saliceti-Piazza, Rodolfo J. Romañach, Luis Ríos, Sandra L. Maldonado-Ramírez

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Biopharmaceuticals manufacturing is one of the major economic activities worldwide. Ninety-three percent of the workforce in a biomanufacturing environment concentrates in production-related areas. As a result, strategic collaborations between industry and academia are crucial to ensure the availability of knowledgeable workforce needed in an economic region to become competitive in biomanufacturing. In the past decade, our institution has been a key strategic partner with multinational biotechnology companies in supplying science and engineering graduates in the field of industrial biotechnology. Initiatives addressing all levels of the educational pipeline, from K-12 to college to continued education for company employees have been established along a ten-year span. The Amgen BioTalents Program was designed to provide undergraduate science and engineering students with training in biomanufacturing. The areas targeted by this educational program enhance their academic development, since these topics are not part of their traditional science and engineering curricula. The educational curriculum involved the process of producing a biomolecule from the genetic engineering of cells to the production of an especially targeted polypeptide, protein expression and purification, to quality control, and validation. This paper will report and describe the implementation details and outcomes of the first sessions of the program.

Keywords: biomanufacturing curriculum, interdisciplinary learning, workforce development, industry-academia partnering

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Authors: Karen C. Olufokunbi, Odetunji A. Odejobi

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The discourse of this paper is the examination of the generation, accumulation and growth of e-waste in a developing country. Images and other data about computer e-waste were collected using a digital camera, 290 copies of questionnaire and three structured interviews using Obafemi Awolowo University (OAU), Ile-Ife, Nigeria environment as a case study. The numerical data were analysed using R data analysis and process tool. Automata-based techniques and Petri net modeling tool were used to design and simulate a computational model for the recovery of saleable materials from e-waste. The R analysis showed that at a 95 percent confidence level, the computer equipment that will be disposed by 2020 will be 417 units. Compared to the 800 units in circulation in 2014, 50 percent of personal computer components will become e-waste. This indicates that personal computer components were in high demand due to their low costs and will be disposed more rapidly when replaced by new computer equipment Also, 57 percent of the respondents discarded their computer e-waste by throwing it into the garbage bin or by dumping it. The simulated model using Coloured Petri net modelling tool for the process showed that the e-waste dynamics is a forward sequential process in the form of a pipeline meaning that an e-waste recovery of saleable materials process occurs in identifiable discrete stages indicating that e-waste will continue to accumulate and grow in volume with time.

Keywords: Coloured Petri net, computational modelling, electronic waste, electronic waste process dynamics

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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: Jafar Ahmadi, Nafiseh Noormohammadi, Sedegeh Fabriki Ourang

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GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare, and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ, and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: domain, gene family, GRF, motif

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Authors: Pingping Zhang, Yanpeng Cai, Jianlong Wang

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Stormwater storage tank (SST) is a popular low impact development technology for reducing stormwater runoff in the construction of sponge city. At present, it is difficult to perform the automatic control of SST for reducing peak flow. In this paper, fuzzy control was introduced into the peak control of SST to improve the efficiency of reducing stormwater runoff. Firstly, the design of SST was investigated. A catchment area and a return period were assumed, a SST model was manufactured, and then the storage capacity of the SST was verified. Secondly, the control parameters of the SST based on reducing stormwater runoff were analyzed, and a schematic diagram of real-time control (RTC) system based on peak control SST was established. Finally, fuzzy control system of a double input (flow and water level) and double output (inlet and outlet valve) was designed. The results showed that 1) under the different return periods (one year, three years, five years), the SST had the effect of delayed peak control and storage by increasing the detention time, 2) rainfall, pipeline flow, the influent time and the water level in the SST could be used as RTC parameters, and 3) the response curves of flow velocity and water level fluctuated very little and reached equilibrium in a short time. The combination of online monitoring and fuzzy control was feasible to control the SST automatically. This paper provides a theoretical reference for reducing stormwater runoff and improving the operation efficiency of SST.

Keywords: stormwater runoff, stormwater storage tank, real-time control, fuzzy control

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Authors: Richard K. Jolley, Jonathan A. Coffman

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Since Enterococci has been implicated in oral disease, we hypothesized the transmission of avian Enterococci to humans via fecal-oral transmission facilitated by adherence to dental plaque. To demonstrate the capability of Enterococci to bind to a dental plaque we filtered avian excreta and incubated the filtrate on a sucrose-induced, Streptococcus mutans biofilm. The biofilm was washed several times with a detergent to remove bacteria binding non-specifically to the biofilm, DNA was isolated from the biofilm, 16S rDNA was amplified, sequenced by Ion Torrent DNA sequencing and analyzed with bioinformatics. Enterococci and other known bacterial pathogens were shown to adhere to the biofilm. Culturing the washed biofilm with Bile Esculin Azide (BEA) agar also confirmed the presence of Enterococci as verified with Sanger sequencing. The results suggest that Enteroccoci in avian excreta has the ability to adhere to human dental plaque and may be a mechanism of entry when humans encounter contaminated aerosols, water or food.

Keywords: Enterococci, avian excreta, dental plaque, NGS

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Authors: Teresa Azevedo PerdicoúLis, Paulo Lopes Dos Santos

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The conceptualisation of the problem of network optimisation as a noncooperative game sets up a holistic interactive approach that brings together different network features (e.g., com-pressor stations, sources, and pipelines, in the gas context) where the optimisation objectives are different, and a single optimisation procedure becomes possible without having to feed results from diverse software packages into each other. A mathematical model of this type, where independent entities take action, offers the ideal modularity and subsequent problem decomposition in view to design a decentralised algorithm to optimise the operation and management of the network. In a game framework, compressor stations and sources are under-stood as players which communicate through network connectivity constraints–the pipeline model. That is, in a scheme similar to tatonnementˆ, the players appoint their best settings and then interact to check for network feasibility. The devolved degree of network unfeasibility informs the players about the ’quality’ of their settings, and this two-phase iterative scheme is repeated until a global optimum is obtained. Due to network transients, its optimisation needs to be assessed at different points of the control interval. For this reason, the proposed approach to optimisation has two stages: (i) the first stage computes along the period of optimisation in order to fulfil the requirement just mentioned; (ii) the second stage is initialised with the solution found by the problem computed at the first stage, and computes in the end of the period of optimisation to rectify the solution found at the first stage. The liability of the proposed scheme is proven correct on an abstract prototype and three example networks.

Keywords: connectivity matrix, gas network optimisation, large-scale, noncooperative game, system decomposition

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Authors: Amir Alani, Mojtaba Mahmoodian, Anna Romanova, Asaad Faramarzi

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Pipelines are extensively used engineering structures which convey fluid from one place to another. Most of the time, pipelines are placed underground and are encumbered by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on concrete pipes in sewage systems (concrete sewers). This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of this type of pipe. Then three probabilistic time dependent reliability analysis methods including the first passage probability theory, the gamma distributed degradation model and the Monte Carlo simulation technique are discussed and developed. Sensitivity analysis indexes which can be used to identify the most important parameters that affect pipe failure are also discussed. The reliability analysis methods developed in this paper contribute as rational tools for decision makers with regard to the strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the sewer system.

Keywords: reliability analysis, service life prediction, Monte Carlo simulation method, first passage probability theory, gamma distributed degradation model

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Authors: Esam I. Jassim

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The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.

Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner

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Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.

Keywords: health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics

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Authors: Prateek Rastogi

Abstract:

Medical teaching in present era concentrates not only on teaching but on effective teaching. For effective teaching a combination of effective carefully designed curriculum, an educated educator, competent learner and fool proof evaluation system is required. Keeping these parameters in mind and study was undertaken at Kasturba Medical College, Mangalore among medical students. In this study, evaluation of Forensic Medicine syllabus along with its teaching and evaluation methodology was done using 20 different parameters. This questionnaire based study was done over a period of two years i.e. 2013 and 2014. Batch of students who just passed the forensic medicine subject was included for study. Carefully designed questionnaire contained questions related to course content, teaching methodology and evaluation system along with provisions to mention merits and demerits of subject. The feedbacks in first round were analyzed and suggestions were implemented before conducting the second round of study. Overall evaluation of course was done as well as it was compared with other subjects of second MBBS. It was noted that Scores improved in 2nd survey thus stressing the importance of course evaluation and student feedback in teaching improvement.

Keywords: teaching methodology, system of evaluation, course content, bioinformatics, biomedicine

Procedia PDF Downloads 357

Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

Abstract:

This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem

Procedia PDF Downloads 166

Authors: Yiding Qu, Svetlana V. Komarova

Abstract:

Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.

Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer

Procedia PDF Downloads 469