Search results for: gene regulatory network

Authors: Umang Varshney, Amit Karamchandani, Rohit Kapoor

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Practitioners and researchers have realized that Blockchain is not limited to currency. Blockchain as a distributed ledger can ensure a transparent and traceable supply chain. Due to Blockchain-enabled IoTs, a firm’s information management system can now take inputs from other supply chain partners in real-time. This study aims to provide empirical evidence of dimensions responsible for blockchain implemented firm’s growth and highlight how sector (manufacturing or service), state's regulatory environment, and choice of blockchain network affect the blockchain's usefulness. This post-adoption study seeks to validate the findings of pre-adoption studies done on the blockchain. Data will be collected through a survey of managers working in blockchain implemented firms and analyzed through PLS-SEM.

Keywords: blockchain, information management system, PLS-SEM, firm's growth

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Authors: Kyoko Tominaga

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Non-Government Organizations (NGOs), Non-Profit Organizations (NPOs), Social Enterprises and other actors play an important role in political decisions in governments at the international levels. Especially, such organizations’ and activists’ network in civil society is quite important to effect to the global politics. To solve the complex social problems in global era, diverse actors should corporate each other. Moreover, network of protesters is also contributes to diffuse tactics, information and other resources of social movements. Based on the findings from the study of International Trade Fairs (ITFs), the author analyzes the network of activists in anti-globalism movement. This research focuses the transition of 54 activists’ whole network in the “protest event” against 2008 G8 summit in Japan. Their network is examined at the three periods: Before protest event phase, during protest event phase and after event phase. A mixed method is used in this study: the author shows the hypothesis from social network analysis and evaluates that with interview data analysis. This analysis gives the two results. Firstly, the more protesters participate to the various events during the protest event, the more they build the network. After that, active protesters keep their network as well. From interview data, we can understand that the active protesters can build their network and diffuse the information because they communicate with other participants and understand that diverse issues are related. This paper comes to same conclusion with previous researches: protest events activate the network among the political activists. However, some participants succeed to build their network, others do not. “Networked” activists are participated in the various events for short period of time and encourage the diffusion of information and tactics of social movements.

Keywords: social movement, global justice movement, tactics, diffusion

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Authors: Rashmi Tamhankar, Madhav Bapat

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In many projects, we have to use human judgment for determining the duration of the activities which may vary from person to person. Hence, there is vagueness about the time duration for activities in network planning. Fuzzy sets can handle such vague or imprecise concepts and has an application to such network. The vague activity times can be represented by triangular fuzzy numbers. In this paper, a general network with fuzzy activity times is considered and conditions for the critical path are obtained also we compute total float time of each activity. Several numerical examples are discussed.

Keywords: PERT, CPM, triangular fuzzy numbers, fuzzy activity times

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Authors: Ewelina Wisnik, Zsolt Regdon, Kinga Chmielewska, Laszlo Virag, Agnieszka Robaszkiewicz

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Apart from protecting genome, PARP1 has been documented to regulate many intracellular processes inter alia gene transcription by physically interacting with chromatin bound proteins and by their ADP-ribosylation. Our recent findings indicate that expression of PARP1 decreases during the differentiation of human CD34+ hematopoietic stem cells to monocytes as a consequence of differentiation-associated cell growth arrest and formation of E2F4-RBL2-HDAC1-SWI/SNF repressive complex at the promoter of this gene. Since the RBL2 complexes repress genes in a E2F-dependent manner and are widespread in the genome in G0 arrested cells, we asked (a) if RBL2 directly contributes to defining monocyte phenotype and function by targeting gene promoters and (b) if RBL2 controls gene transcription indirectly by repressing PARP1. For identification of genes controlled by RBL2 and/or PARP1,we used primer libraries for surface receptors and TLR signaling mediators, genes were silenced by siRNA or shRNA, analysis of gene promoter occupation by selected proteins was carried out by ChIP-qPCR, while statistical analysis in GraphPad Prism 5 and STATISTICA, ChIP-Seq data were analysed in Galaxy 2.5.0.0. On the list of 28 genes regulated by RBL2, we identified only four solely repressed by RBL2-E2F4-HDAC1-BRM complex. Surprisingly, 24 out of 28 emerged genes controlled by RBL2 were co-regulated by PARP1 in six different manners. In one mode of RBL2/PARP1 co-operation, represented by MAP2K6 and MAPK3, PARP1 was found to associate with gene promoters upon RBL2 silencing, which was previously shown to restore PARP1 expression in monocytes. PARP1 effect on gene transcription was observed only in the presence of active EP300, which acetylated gene promoters and activated transcription. Further analysis revealed that PARP1 binding to MA2K6 and MAPK3 promoters enabled recruitment of EP300 in monocytes, while in proliferating cancer cell lines, which actively transcribe PARP1, this protein maintained EP300 at the promoters of MA2K6 and MAPK3. Genome-wide analysis revealed a similar distribution of PARP1 and EP300 around transcription start sites and the co-occupancy of some gene promoters by PARP1 and EP300 in cancer cells. Here, we described a new RBL2/PARP1/EP300 axis which controls gene transcription regardless of the cell type. In this model cell, cycle-dependent transcription of PARP1 regulates expression of some genes repressed by RBL2 upon cell cycle limitation. Thus, RBL2 may indirectly regulate transcription of some genes by controlling the expression of EP300-recruiting PARP1. Acknowledgement: This work was financed by Polish National Science Centre grants nr DEC-2013/11/D/NZ2/00033 and DEC-2015/19/N/NZ2/01735. L.V. is funded by the National Research, Development and Innovation Office grants GINOP-2.3.2-15-2016-00020 TUMORDNS, GINOP-2.3.2-15-2016-00048-STAYALIVE and OTKA K112336. AR is supported by Polish Ministry of Science and Higher Education 776/STYP/11/2016.

Keywords: retinoblastoma transcriptional co-repressor like 2 (RBL2), poly(ADP-ribose) polymerase 1 (PARP1), E1A binding protein p300 (EP300), monocytes

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Authors: Muhammad Kamran Asif

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MPLS stands for Multi-Protocol Label Switching. It is the technology which replaces ATM (Asynchronous Transfer Mode) and frame relay. In this paper, we have designed a full fledge small scale MPLS based service provider network core network model, which provides communication services (e.g. voice, video and data) to the customer more efficiently using label switching technique. Using MPLS VPN provides security to the customers which are either on LAN or WAN. It protects its single customer sites from being attacked by any intruder from outside world along with the provision of concept of extension of a private network over an internet. In this paper, we tried to implement a service provider network using minimum available resources i.e. five 3800 series CISCO routers comprises of service provider core, provider edge routers and customer edge routers. The customers on the one end of the network (customer side) is capable of sending any kind of data to the customers at the other end using service provider cloud which is MPLS VPN enabled. We have also done simulation and emulation for the model using GNS3 (Graphical Network Simulator-3) and achieved the real time scenarios. We have also deployed a NMS system which monitors our service provider cloud and generates alarm in case of any intrusion or malfunctioning in the network. Moreover, we have also provided a video help desk facility between customers and service provider cloud to resolve the network issues more effectively.

Keywords: MPLS, VPN, NMS, ATM, asynchronous transfer mode

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Authors: Juha Kettunen

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This study analyzes the quality and the size of the strategic network of higher education institutions. The study analyses the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented of the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: balanced scorecard, higher education, social networking, strategic planning

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Authors: Kah Yan How, Peh Fern Ong, Keang Peng Song

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Porphyromonas gingivalis is a black-pigmented, anaerobic Gram-negative bacterium that is important in the progression of chronic and severe periodontitis. This organism has an essential requirement for iron, which is usually obtained from hemin, using specific membrane receptors, proteases, and lipoproteins. In this study, we report the characterization of a novel 24 kDa hemin-binding protein, HmuX, in P. gingivalis W50. The hmuX gene is 651 bp long which encodes for a 217 amino acid protein. HmuX was found to be identical at the C-terminus to the previously reported HmuY protein, differing by an additional 74 amino acids at the N-terminus. Recombinant HmuX demonstrated hemin-binding ability by LDS- PAGE and TMBZ staining. Sequence analysis of HmuX revealed a putative lipoprotein attachment site, suggesting its possible role as a lipoprotein. HmuX was also localized to the outer cell surface by transmission electron microscopy. Northern analysis showed hmuX to be transcribed as a single gene and that hmuX mRNA was tightly regulated by the availability of extra-cellular hemin. P. gingivalis isogenic mutant deficient in hmuX gene exhibited significant growth retardation under hemin-limited conditions. Taken together, these results suggest that HmuX is a hemin-binding lipoprotein, important in hemin utilization for the growth of P. gingivalis.

Keywords: Porphyromonas gingivalis, periodontal diseases, HmuX, protein characterization

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Authors: Vanja Misic, Mohamed El-Mogy, Yousef Haj-Ahmad

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Endonuclease G (EndoG) is a well conserved mitochondrio-nuclear nuclease with dual lethal and vital roles in the cell. The aim of our study was to examine whether EndoG exerts its nuclease activity on exogenous DNA substrates such as plasmid DNA (pDNA), considering their importance in gene therapy applications. The effects of EndoG knockdown on pDNA stability and levels of encoded reporter gene expression were evaluated in the cervical carcinoma HeLa cells. Transfection of pDNA vectors encoding short-hairpin RNAs (shRNAs) reduced levels of EndoG mRNA and nuclease activity in HeLa cells. In physiological circumstances, EndoG knockdown did not have an effect on the stability of pDNA or the levels of encoded transgene expression as measured over a four day time-course. However, when endogenous expression of EndoG was induced by an extrinsic stimulus, targeting of EndoG by shRNA improved the perceived stability and transgene expression of pDNA vectors. Therefore, EndoG is not a mediator of exogenous DNA clearance, but in non-physiological circumstances it may non-specifically cleave intracellular DNA regardless of its origin. These findings make it unlikely that targeting of EndoG is a viable strategy for improving the duration and level of transgene expression from non-viral DNA vectors in gene therapy efforts.

Keywords: EndoG, silencing, exogenous DNA stability, HeLa cells

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Authors: Semanur Soyyigit Kaya, Ercan Eren

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Energy has a prominent role for development of nations. Countries which have energy resources also have strategic power in the international trade of energy since it is essential for all stages of production in the economy. Thus, it is important for countries to analyze the weakness and strength of the system. On the other side, it is commonly believed that international trade has complex network properties. Complex network is a tool for the analysis of complex systems with heterogeneous agents and interaction between them. A complex network consists of nodes and the interactions between these nodes. Total properties which emerge as a result of these interactions are distinct from the sum of small parts (more or less) in complex systems. Thus, standard approaches to international trade are superficial to analyze these systems. Network analysis provides a new approach to analyze international trade as a network. In this network countries constitute nodes and trade relations (export or import) constitute edges. It becomes possible to analyze international trade network in terms of high degree indicators which are specific to complex systems such as connectivity, clustering, assortativity/disassortativity, centrality, etc. In this analysis, international trade of crude oil and coal which are types of fossil fuel has been analyzed from 2005 to 2014 via network analysis. First, it has been analyzed in terms of some topological parameters such as density, transitivity, clustering etc. Afterwards, fitness to Pareto distribution has been analyzed. Finally, weighted HITS algorithm has been applied to the data as a centrality measure to determine the real prominence of countries in these trade networks. Weighted HITS algorithm is a strong tool to analyze the network by ranking countries with regards to prominence of their trade partners. We have calculated both an export centrality and an import centrality by applying w-HITS algorithm to data.

Keywords: complex network approach, fossil fuel, international trade, network theory

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Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

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Complexity science seeks the understanding of systems adopting diverse theories from various areas. Network analysis has been gaining space and credibility, namely with the biological, social and economic systems. Significant part of the literature focuses only monolayer representations of connections among agents considering one level of their relationships, and excludes other levels of interactions, leading to simplistic results in network analysis. Therefore, this work aims to demonstrate the advantages of the use of multilayer networks for the representation and analysis of networks. For this, we analyzed an interbank network, composed of 42 banks, comparing the centrality measures of the agents (degree and PageRank) resulting from each method (monolayer x multilayer). This proved to be the most reliable and efficient the multilayer analysis for the study of the current networks and highlighted JP Morgan and Deutsche Bank as the most important banks of the analyzed network.

Keywords: complexity, interbank networks, multilayer networks, network analysis

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Authors: J. K. Alhassan, C. S. Actsu

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This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

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Authors: Chi-Ching Lee, Po-Jung Huang, Kuo-Yang Huang, Petrus Tang

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Background: Recent advances in high-throughput research technologies such as new-generation sequencing and multi-dimensional liquid chromatography makes it possible to dissect the complete transcriptome and proteome in a single run for the first time. However, it is almost impossible for many laboratories to handle and analysis these “BIG” data without the support from a bioinformatics team. We aimed to provide a web-based analysis platform for users with only limited knowledge on bio-computing to study the functional genomics and proteomics. Method: We use NCI-60 as an example dataset to demonstrate the power of the web-based analysis platform and data delivering system: C-eXpress takes a simple text file that contain the standard NCBI gene or protein ID and expression levels (rpkm or fold) as input file to generate a distribution map of gene/protein expression levels in a heatmap diagram organized by color gradients. The diagram is hyper-linked to a dynamic html table that allows the users to filter the datasets based on various gene features. A dynamic summary chart is generated automatically after each filtering process. Results: We implemented an integrated database that contain pre-defined annotations such as gene/protein properties (ID, name, length, MW, pI); pathways based on KEGG and GO biological process; subcellular localization based on GO cellular component; functional classification based on GO molecular function, kinase, peptidase and transporter. Multiple ways of sorting of column and rows is also provided for comparative analysis and visualization of multiple samples.

Keywords: cancer, visualization, database, functional annotation

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Authors: Paola Modesto, Floriana Fruscione, Isabella Martini, Simona Perga, Federica Riccardo, Mariateresa Camerino, Davide Giacobino, Cecilia Gola, Luca Licenziato, Elisabetta Razzuoli, Katia Varello, Lorella Maniscalco, Elena Bozzetta, Angelo Ferrari

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Canine and human melanoma, osteosarcoma (OSA), and mammary carcinomas are aggressive tumors with common characteristics making dogs a good model for comparative oncology. Novel therapeutic strategies against these tumors could be useful to both species. In humans, chondroitin sulphate proteoglycan 4 (CSPG4) is a marker involved in tumor progression and could be a candidate target for immunotherapy. The anti-CSPG4 DNA electrovaccination has shown to be an effective approach for canine malignant melanoma (CMM) [1]. An immunohistochemistry evaluation of CSPG4 expression in tumour tissue is generally performed prior to electrovaccination. To assess the possibility to perform a rapid molecular evaluation and in order to validate these spontaneous canine tumors as the model for human studies, we investigate the CSPG4 gene expression by RT qPCR in CMM, OSA, and canine mammary tumors (CMT). The total RNA was extracted from RNAlater stored tissue samples (CMM n=16; OSA n=13; CMT n=6; five paired normal tissues for CMM, five paired normal tissues for OSA and one paired normal tissue for CMT), retro-transcribed and then analyzed by duplex RT-qPCR using two different TaqMan assays for the target gene CSPG4 and the internal reference gene (RG) Ribosomal Protein S19 (RPS19). RPS19 was selected from a panel of 9 candidate RGs, according to NormFinder analysis following the protocol already described [2]. Relative expression was analyzed by CFX Maestro™ Software. Student t-test and ANOVA were performed (significance set at P<0.05). Results showed that gene expression of CSPG4 in OSA tissues is significantly increased by 3-4 folds when compared to controls. In CMT, gene expression of the target was increased from 1.5 to 19.9 folds. In melanoma, although an increasing trend was observed, no significant differences between the two groups were highlighted. Immunohistochemistry analysis of the two cancer types showed that the expression of CSPG4 within CMM is concentrated in isles of cells compared to OSA, where the distribution of positive cells is homogeneous. This evidence could explain the differences in gene expression results.CSPG4 immunohistochemistry evaluation in mammary carcinoma is in progress. The evidence of CSPG4 expression in a different type of canine tumors opens the way to the possibility of extending the CSPG4 immunotherapy marker in CMM, OSA, and CMT and may have an impact to translate this strategy modality to human oncology.

Keywords: canine melanoma, canine mammary carcinomas, canine osteosarcoma, CSPG4, gene expression, immunotherapy

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Authors: Meiling Yu, Nadia Rouatbi, Khuloud T. Al-Jamal

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Background: Treatment of neurological disorders with modern medical and surgical approaches remains difficult. Gene therapy, allowing the delivery of genetic materials that encodes potential therapeutic molecules, represents an attractive option. The treatment of brain diseases with gene therapy requires the gene-editing tool to be delivered efficiently to the central nervous system. In this study, we explored the efficiency of different delivery routes, namely intravenous (i.v.), intra-cranial (i.c.), and intra-nasal (i.n.), to deliver stable nucleic acid-lipid particles (SNALPs) containing gene-editing tools namely Cas9 mRNA and sgRNA encoding for GFP as a reporter protein. We hypothesise that SNALPs can reach the brain and perform gene-editing to different extents depending on the administration route. Intranasal administration (i.n.) offers an attractive and non-invasive way to access the brain circumventing the blood–brain barrier. Successful delivery of gene-editing tools to the brain offers a great opportunity for therapeutic target validation and nucleic acids therapeutics delivery to improve treatment options for a range of neurodegenerative diseases. In this study, we utilised Rosa26-Cas9 knock-in mice, expressing GFP, to study brain distribution and gene-editing efficiency of SNALPs after i.v.; i.c. and i.n. routes of administration. Methods: Single guide RNA (sgRNA) against GFP has been designed and validated by in vitro nuclease assay. SNALPs were formulated and characterised using dynamic light scattering. The encapsulation efficiency of nucleic acids (NA) was measured by RiboGreen™ assay. SNALPs were incubated in serum to assess their ability to protect NA from degradation. Rosa26-Cas9 knock-in mice were i.v., i.n., or i.c. administered with SNALPs to test in vivo gene-editing (GFP knockout) efficiency. SNALPs were given as three doses of 0.64 mg/kg sgGFP following i.v. and i.n. or a single dose of 0.25 mg/kg sgGFP following i.c.. knockout efficiency was assessed after seven days using Sanger Sequencing and Inference of CRISPR Edits (ICE) analysis. In vivo, the biodistribution of DiR labelled SNALPs (SNALPs-DiR) was assessed at 24h post-administration using IVIS Lumina Series III. Results: Serum-stable SNALPs produced were 130-140 nm in diameter with ~90% nucleic acid loading efficiency. SNALPs could reach and stay in the brain for up to 24h following i.v.; i.n. and i.c. administration. Decreasing GFP expression (around 50% after i.v. and i.c. and 20% following i.n.) was confirmed by optical imaging. Despite the small number of mice used, ICE analysis confirmed GFP knockout in mice brains. Additional studies are currently taking place to increase mice numbers. Conclusion: Results confirmed efficient gene knockout achieved by SNALPs in Rosa26-Cas9 knock-in mice expressing GFP following different routes of administrations in the following order i.v.= i.c.> i.n. Each of the administration routes has its pros and cons. The next stages of the project involve assessing gene-editing efficiency in wild-type mice and replacing GFP as a model target with therapeutic target genes implicated in Motor Neuron Disease pathology.

Keywords: CRISPR, nanoparticles, brain diseases, administration routes

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Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: Saulius Minkevicius, Edvinas Greicius

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The paper is devoted to the analysis of queueing systems in the context of the network and communications theory. We investigate the inequality in an open queueing network and its applications to the theorems in heavy traffic conditions (fluid approximation, functional limit theorem, and law of the iterated logarithm) for a queue of customers in an open queueing network.

Keywords: fluid approximation, heavy traffic, models of information systems, open queueing network, queue length of customers, queueing theory

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Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

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Authors: Che Z. Zulkifli, Nursyahida M. Noor, Siti N. Semunab, Shafawati A. Malek

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Wireless sensors, also known as wireless sensor nodes, have been making a significant impact on human daily life. The Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two complementary technologies; hence, an integrated implementation of these technologies expands the overall functionality in obtaining long-range and real-time information on the location and properties of objects and people. An approach for integrating ZigBee and RFID networks is proposed in this paper, to create an energy-efficient network improved by the benefits of combining ZigBee and RFID architecture. Furthermore, the compatibility and requirements of the ZigBee device and communication links in the typical RFID system which is presented with the real world experiment on the capabilities of the proposed RFID system.

Keywords: mesh network, RFID, wireless sensor network, zigbee

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Authors: Waheed Oseni

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This article reviews emergent global trends in intellectual property protection and identifies patenting as a strategic initiative. Recent developments in software and method of doing business patenting are fast transforming the e‐business landscape. The article discusses the emergent global regulatory framework concerning intellectual property rights and the strategic value of patenting. Important features of a corporate patenting portfolio are described. Superficially, the e‐commerce landscape appears to be dominated by dotcom start-ups or the “dotcomization” of existing brick and mortar companies. But, in reality, at its very bedrock is intellectual property (IP). In this connection, the recent avalanche of patenting of software and method‐of‐doing‐business (MDB) in the USA is a very significant development with regard to rules governing IP rights and, therefore, e‐commerce. Together with the World Trade Organization’s (WTO) IP rules, there is an emerging global regulatory framework for IP rights, an understanding of which is necessary for designing effective e‐commerce strategies.

Keywords: intellectual property, patents, methods, computer software

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Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of varied species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: adaptation, animals, evolution, genomics

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Authors: Contimi Kenfack Mouafo, Sebastian Klick

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In the rural and remote areas of Cameroon, access to electricity is very limited since most of the population is not connected to the main utility grid. Throughout the country, efforts are underway to not only expand the utility grid to these regions but also to provide reliable off-grid access to electricity. The Cameroonian company Solahydrowatt is currently working on the design and planning of one of the first hybrid solar-hydropower plants of Cameroon in Fotetsa, in the western region of the country, to provide the population with reliable access to electricity. This paper models and proposes a design for the low-voltage network with a hybrid solar-hydropower plant in Fotetsa. The modelling takes into consideration the voltage compliance of the distribution network, the maximum load of operating equipment, and most importantly, the ability for the network to operate as an off-grid system. The resulting modelled distribution network does not only comply with the Cameroonian voltage deviation standard, but it is also capable of being operated as a stand-alone network independent of the main utility grid.

Keywords: Cameroon, rural electrification, hybrid solar-hydro, off-grid electricity supply, network simulation

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Authors: Noman Shabbir, Roheel Nawaz, Muhammad N. Iqbal, Junaid Zafar

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This paper focuses on the performance evaluation of routing protocols in WLAN based Wireless Sensor Networks (WSNs). A comparative analysis of routing protocols such as Ad-hoc On-demand Distance Vector Routing System (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR) is been made against different network parameters like network load, end to end delay and throughput in small, medium and large-scale sensor network scenarios to identify the best performing protocol. Simulation results indicate that OLSR gives minimum network load in all three scenarios while AODV gives the best throughput in small scale network but in medium and large scale networks, DSR is better. In terms of delay, OLSR is more efficient in small and medium scale network while AODV is slightly better in large networks.

Keywords: WLAN, WSN, AODV, DSR, OLSR

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Authors: Saima Suleman, Kalsoom Sughra, Naeem Mahmood Ashraf

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Mycobacterium tuberculosis is a communicable chronic illness. This disease is being highly focused by researchers as it is present approximately in one third of world population either in active or latent form. The genetic makeup of a person plays an important part in producing immunity against disease. And one important factor association is single nucleotide polymorphism of relevant gene. In this study, we have studied association between single nucleotide polymorphism of CD-209 gene (encode DC-SIGN receptor) and patients of tuberculosis. Dry lab (in silico) and wet lab (RFLP) analysis have been carried out. GWAS catalogue and GEO database have been searched to find out previous association data. No association study has been found related to CD-209 nsSNPs but role of CD-209 in pulmonary tuberculosis have been addressed in GEO database.Therefore, CD-209 has been selected for this study. Different databases like ENSEMBLE and 1000 Genome Project has been used to retrieve SNP data in form of VCF file which is further submitted to different software to sort SNPs into benign and deleterious. Selected SNPs are further annotated by using 3-D modeling techniques using I-TASSER online software. Furthermore, selected nsSNPs were checked in Gujrat and Faisalabad population through RFLP analysis. In this study population two SNPs are found to be associated with tuberculosis while one nsSNP is not found to be associated with the disease.

Keywords: association, CD209, DC-SIGN, tuberculosis

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Skiker Kaoutar, Mounir Maouene

Abstract:

Neuroimaging studies indicate that a large fronto-parieto-temporal network support nouns and their features, with some areas store semantic knowledge (visual, auditory, olfactory, gustatory,…), other areas store lexical representation and other areas are implicated in general semantic processing. However, it is not well understood how this fronto-parieto-temporal network can be modulated by different semantic tasks and different semantic relations between nouns. In this study, we combine a behavioral semantic network, functional MRI studies involving object’s related nouns and brain network studies to explain how different semantic tasks and different semantic relations between nouns can modulate the activity within the brain network of nouns and their features. We first describe how nouns and their features form a large scale brain network. For this end, we examine the connectivities between areas recruited during the processing of nouns to know which configurations of interaction areas are possible. We can thus identify if, for example, brain areas that store semantic knowledge communicate via functional/structural links with areas that store lexical representations. Second, we examine how this network is modulated by different semantic tasks involving nouns and finally, we examine how category specific activation may result from the semantic relations among nouns. The results indicate that brain network of nouns and their features is highly modulated and flexible by different semantic tasks and semantic relations. At the end, this study can be used as a guide to help neurosientifics to interpret the pattern of fMRI activations detected in the semantic processing of nouns. Specifically; this study can help to interpret the category specific activations observed extensively in a large number of neuroimaging studies and clinical studies.

Keywords: nouns, features, network, category specificity

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Authors: Masoud Soltanialvar, Ali Bagherpour

Abstract:

The aim of this study was to determinate the variety of Anaplasma species among sheep of khouzestan province, Iran. From April 2013 to June 2013, a total of 200 blood samples were collected via the jugular vein from healthy sheep (100), randomly. The extracted DNA from blood cells were amplified by Anaplasma-all primers, which amplify an approximately 1468bp DNA fragment from region of 16S rRNA gene from various members of the genus Anaplasma. For raising the test sensivity, the PCR products were amplified with the primers, which were designed from the region flanked by the first primers. The amplified nested PCR product had an expected PCR product with 345 nucleotides in length. In 100 sheep blood samples, 7 samples were Anaplasma spp. positive by first PCR and nested PCR. The results showed that 2 of total 100 blood samples (2%) were A.phagocytophilum positive by specific nested PCR based on 16S rRNA gene. The extracted DNA from positive Anaplasma spp. samples were amplified by Anaplasma ovis specific primers, which amplify an approximately 866bp DNA fragment from region of msp4 gene. 5 out of 100 sheep blood samples (5%) were positive for Anaplasma ovis. This study is the first molecular detection of A. ovis and A.phagocytophilum from sheep in Iran.

Keywords: Iran, anaplasma species, sheep, A. ovis, A. phagocytophilum, PCR

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Authors: Liu Zhiyuan, Sun Zongdi

Abstract:

In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network model. Finally, after the training of BP neural network, the prediction values of Shanghai carbon trading price and trading volume are obtained, and the model is tested.

Keywords: Carbon trading price, carbon trading volume, BP neural network model, Shanghai City

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Xiaohan Bookman, Xiaoyan Zhu

Abstract:

Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

Procedia PDF Downloads 328