WorldWideScience

Sample records for sos learning networks

  1. A Small-Molecule Inducible Synthetic Circuit for Control of the SOS Gene Network without DNA Damage.

    Science.gov (United States)

    Kubiak, Jeffrey M; Culyba, Matthew J; Liu, Monica Yun; Mo, Charlie Y; Goulian, Mark; Kohli, Rahul M

    2017-11-17

    The bacterial SOS stress-response pathway is a pro-mutagenic DNA repair system that mediates bacterial survival and adaptation to genotoxic stressors, including antibiotics and UV light. The SOS pathway is composed of a network of genes under the control of the transcriptional repressor, LexA. Activation of the pathway involves linked but distinct events: an initial DNA damage event leads to activation of RecA, which promotes autoproteolysis of LexA, abrogating its repressor function and leading to induction of the SOS gene network. These linked events can each independently contribute to DNA repair and mutagenesis, making it difficult to separate the contributions of the different events to observed phenotypes. We therefore devised a novel synthetic circuit to unlink these events and permit induction of the SOS gene network in the absence of DNA damage or RecA activation via orthogonal cleavage of LexA. Strains engineered with the synthetic SOS circuit demonstrate small-molecule inducible expression of SOS genes as well as the associated resistance to UV light. Exploiting our ability to activate SOS genes independently of upstream events, we further demonstrate that the majority of SOS-mediated mutagenesis on the chromosome does not readily occur with orthogonal pathway induction alone, but instead requires DNA damage. More generally, our approach provides an exemplar for using synthetic circuit design to separate an environmental stressor from its associated stress-response pathway.

  2. Analysis of the SOS response of Vibrio and other bacteria with multiple chromosomes

    Directory of Open Access Journals (Sweden)

    Sanchez-Alberola Neus

    2012-02-01

    Full Text Available Abstract Background The SOS response is a well-known regulatory network present in most bacteria and aimed at addressing DNA damage. It has also been linked extensively to stress-induced mutagenesis, virulence and the emergence and dissemination of antibiotic resistance determinants. Recently, the SOS response has been shown to regulate the activity of integrases in the chromosomal superintegrons of the Vibrionaceae, which encompasses a wide range of pathogenic species harboring multiple chromosomes. Here we combine in silico and in vitro techniques to perform a comparative genomics analysis of the SOS regulon in the Vibrionaceae, and we extend the methodology to map this transcriptional network in other bacterial species harboring multiple chromosomes. Results Our analysis provides the first comprehensive description of the SOS response in a family (Vibrionaceae that includes major human pathogens. It also identifies several previously unreported members of the SOS transcriptional network, including two proteins of unknown function. The analysis of the SOS response in other bacterial species with multiple chromosomes uncovers additional regulon members and reveals that there is a conserved core of SOS genes, and that specialized additions to this basic network take place in different phylogenetic groups. Our results also indicate that across all groups the main elements of the SOS response are always found in the large chromosome, whereas specialized additions are found in the smaller chromosomes and plasmids. Conclusions Our findings confirm that the SOS response of the Vibrionaceae is strongly linked with pathogenicity and dissemination of antibiotic resistance, and suggest that the characterization of the newly identified members of this regulon could provide key insights into the pathogenesis of Vibrio. The persistent location of key SOS genes in the large chromosome across several bacterial groups confirms that the SOS response plays an

  3. Analysis of the SOS response of Vibrio and other bacteria with multiple chromosomes.

    Science.gov (United States)

    Sanchez-Alberola, Neus; Campoy, Susana; Barbé, Jordi; Erill, Ivan

    2012-02-03

    The SOS response is a well-known regulatory network present in most bacteria and aimed at addressing DNA damage. It has also been linked extensively to stress-induced mutagenesis, virulence and the emergence and dissemination of antibiotic resistance determinants. Recently, the SOS response has been shown to regulate the activity of integrases in the chromosomal superintegrons of the Vibrionaceae, which encompasses a wide range of pathogenic species harboring multiple chromosomes. Here we combine in silico and in vitro techniques to perform a comparative genomics analysis of the SOS regulon in the Vibrionaceae, and we extend the methodology to map this transcriptional network in other bacterial species harboring multiple chromosomes. Our analysis provides the first comprehensive description of the SOS response in a family (Vibrionaceae) that includes major human pathogens. It also identifies several previously unreported members of the SOS transcriptional network, including two proteins of unknown function. The analysis of the SOS response in other bacterial species with multiple chromosomes uncovers additional regulon members and reveals that there is a conserved core of SOS genes, and that specialized additions to this basic network take place in different phylogenetic groups. Our results also indicate that across all groups the main elements of the SOS response are always found in the large chromosome, whereas specialized additions are found in the smaller chromosomes and plasmids. Our findings confirm that the SOS response of the Vibrionaceae is strongly linked with pathogenicity and dissemination of antibiotic resistance, and suggest that the characterization of the newly identified members of this regulon could provide key insights into the pathogenesis of Vibrio. The persistent location of key SOS genes in the large chromosome across several bacterial groups confirms that the SOS response plays an essential role in these organisms and sheds light into the

  4. SNAP Operating System (SOS) user's guide

    International Nuclear Information System (INIS)

    Sabuda, J.D.; Polito, J.; Walker, J.L.; Grant, F.H. III.

    1982-03-01

    The SNAP Operating System (SOS) is a FORTRAN 77 program which provides assistance to the safeguards analyst who uses the Safeguards Automated Facility Evaluation (SAFE) and the Safeguards Network Analysis Procedure (SNAP) techniques. Features offered by SOS are a data base system for storing a library of SNAP applications, computer graphics representation of SNAP models, a computer graphics editor to develop and modify SNAP models, a SAFE-to-SNAP interface, automatic generation of SNAP input data, and a computer graphics postprocessor for SNAP. The SOS User's Guide is designed to provide the user with the information necessary to use SOS effectively. Examples are used throughout to illustrate the concepts. The format of the user's guide follows the same sequence as would be used in executing an actual application

  5. Characterization of the SOS meta-regulon in the human gut microbiome.

    Science.gov (United States)

    Cornish, Joseph P; Sanchez-Alberola, Neus; O'Neill, Patrick K; O'Keefe, Ronald; Gheba, Jameel; Erill, Ivan

    2014-05-01

    Data from metagenomics projects remain largely untapped for the analysis of transcriptional regulatory networks. Here, we provide proof-of-concept that metagenomic data can be effectively leveraged to analyze regulatory networks by characterizing the SOS meta-regulon in the human gut microbiome. We combine well-established in silico and in vitro techniques to mine the human gut microbiome data and determine the relative composition of the SOS network in a natural setting. Our analysis highlights the importance of translesion synthesis as a primary function of the SOS response. We predict the association of this network with three novel protein clusters involved in cell wall biogenesis, chromosome partitioning and restriction modification, and we confirm binding of the SOS response transcriptional repressor to sites in the promoter of a cell wall biogenesis enzyme, a phage integrase and a death-on-curing protein. We discuss the implications of these findings and the potential for this approach for metagenome analysis.

  6. Non-equilibrium repressor binding kinetics link DNA damage dose to transcriptional timing within the SOS gene network.

    Science.gov (United States)

    Culyba, Matthew J; Kubiak, Jeffrey M; Mo, Charlie Y; Goulian, Mark; Kohli, Rahul M

    2018-06-01

    Biochemical pathways are often genetically encoded as simple transcription regulation networks, where one transcription factor regulates the expression of multiple genes in a pathway. The relative timing of each promoter's activation and shut-off within the network can impact physiology. In the DNA damage repair pathway (known as the SOS response) of Escherichia coli, approximately 40 genes are regulated by the LexA repressor. After a DNA damaging event, LexA degradation triggers SOS gene transcription, which is temporally separated into subsets of 'early', 'middle', and 'late' genes. Although this feature plays an important role in regulating the SOS response, both the range of this separation and its underlying mechanism are not experimentally defined. Here we show that, at low doses of DNA damage, the timing of promoter activities is not separated. Instead, timing differences only emerge at higher levels of DNA damage and increase as a function of DNA damage dose. To understand mechanism, we derived a series of synthetic SOS gene promoters which vary in LexA-operator binding kinetics, but are otherwise identical, and then studied their activity over a large dose-range of DNA damage. In distinction to established models based on rapid equilibrium assumptions, the data best fit a kinetic model of repressor occupancy at promoters, where the drop in cellular LexA levels associated with higher doses of DNA damage leads to non-equilibrium binding kinetics of LexA at operators. Operators with slow LexA binding kinetics achieve their minimal occupancy state at later times than operators with fast binding kinetics, resulting in a time separation of peak promoter activity between genes. These data provide insight into this remarkable feature of the SOS pathway by demonstrating how a single transcription factor can be employed to control the relative timing of each gene's transcription as a function of stimulus dose.

  7. SOS, the formidable strategy of bacteria against aggressions.

    Science.gov (United States)

    Baharoglu, Zeynep; Mazel, Didier

    2014-11-01

    The presence of an abnormal amount of single-stranded DNA in the bacterial cell constitutes a genotoxic alarm signal that induces the SOS response, a broad regulatory network found in most bacterial species to address DNA damage. The aim of this review was to point out that beyond being a repair process, SOS induction leads to a very strong but transient response to genotoxic stress, during which bacteria can rearrange and mutate their genome, induce several phenotypic changes through differential regulation of genes, and sometimes acquire characteristics that potentiate bacterial survival and adaptation to changing environments. We review here the causes and consequences of SOS induction, but also how this response can be modulated under various circumstances and how it is connected to the network of other important stress responses. In the first section, we review articles describing the induction of the SOS response at the molecular level. The second section discusses consequences of this induction in terms of DNA repair, changes in the genome and gene expression, and sharing of genomic information, with their effects on the bacteria's life and evolution. The third section is about the fine tuning of this response to fit with the bacteria's 'needs'. Finally, we discuss recent findings linking the SOS response to other stress responses. Under these perspectives, SOS can be perceived as a powerful bacterial strategy against aggressions. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  8. SNAP/SOS: a package for simulating and analyzing safeguards systems

    International Nuclear Information System (INIS)

    Grant, F.H. III; Polito, J.; Sabuda, J.

    1983-01-01

    The effective analysis of safeguards systems at nuclear facilities requires significant effort. The Safeguards Network Analysis Procedure (SNAP) and the SNAP Operating System (SOS) reduce that effort to a manageable level. SNAP provides a detailed analysis of site safeguards for tactical evaluation. SOS helps the analyst organize and manage the SNAP effort effectively. SOS provides a database for model storage, automatic model generation, and computer graphics. The SOS/SNAP combination is a working example of a simulation system including executive-level control, database system, and facilities for model creation, editing, and output analysis

  9. SOS response and its regulation on the fluoroquinolone resistance.

    Science.gov (United States)

    Qin, Ting-Ting; Kang, Hai-Quan; Ma, Ping; Li, Peng-Peng; Huang, Lin-Yan; Gu, Bing

    2015-12-01

    Bacteria can survive fluoroquinolone antibiotics (FQs) treatment by becoming resistant through a genetic change-mutation or gene acquisition. The SOS response is widespread among bacteria and exhibits considerable variation in its composition and regulation, which is repressed by LexA protein and derepressed by RecA protein. Here, we take a comprehensive review of the SOS gene network and its regulation on the fluoroquinolone resistance. As a unique survival mechanism, SOS may be an important factor influencing the outcome of antibiotic therapy in vivo.

  10. Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics

    Science.gov (United States)

    Chen, Lei; Kou, Yingxin; Li, Zhanwu; Xu, An; Wu, Cheng

    2018-01-01

    We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core-periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes.

  11. An orthosteric inhibitor of the RAS-SOS interaction.

    Science.gov (United States)

    Nickerson, Seth; Joy, Stephen T; Arora, Paramjit S; Bar-Sagi, Dafna

    2013-01-01

    Rat sarcoma (RAS) proteins are signaling nodes that transduce extracellular cues into precise alterations in cellular physiology by engaging effector pathways. RAS signaling thus regulates diverse cell processes including proliferation, migration, differentiation, and survival. Owing to this central role in governing mitogenic signals, RAS pathway components are often dysregulated in human diseases. Targeted therapy of RAS pathways has generally not been successful, largely because of the robust biochemistry of the targets and their multifaceted network of molecular regulators. The rate-limiting step of RAS activation is Son of Sevenless (SOS)-mediated nucleotide exchange involving a single evolutionarily conserved catalytic helix from SOS. Structure function data of this mechanism provided a strong platform to design an SOS-derived, helically constrained peptide mimic as an inhibitor of the RAS-SOS interaction. In this chapter, we review RAS-SOS signaling dynamics and present evidence supporting the novel paradigm of inhibiting their interaction as a therapeutic strategy. We then describe a method of generating helically constrained peptide mimics of protein surfaces, which we have employed to inhibit the RAS-SOS active site interaction. The biochemical and functional properties of this SOS mimic support the premise that inhibition of RAS-nucleotide exchange can effectively block RAS activation and downstream signaling. © 2013 Elsevier Inc. All rights reserved.

  12. The Salt Overly Sensitive (SOS) pathway: established and emerging roles.

    Science.gov (United States)

    Ji, Hongtao; Pardo, José M; Batelli, Giorgia; Van Oosten, Michael J; Bressan, Ray A; Li, Xia

    2013-03-01

    Soil salinity is a growing problem around the world with special relevance in farmlands. The ability to sense and respond to environmental stimuli is among the most fundamental processes that enable plants to survive. At the cellular level, the Salt Overly Sensitive (SOS) signaling pathway that comprises SOS3, SOS2, and SOS1 has been proposed to mediate cellular signaling under salt stress, to maintain ion homeostasis. Less well known is how cellularly heterogenous organs couple the salt signals to homeostasis maintenance of different types of cells and to appropriate growth of the entire organ and plant. Recent evidence strongly indicates that different regulatory mechanisms are adopted by roots and shoots in response to salt stress. Several reports have stated that, in roots, the SOS proteins may have novel roles in addition to their functions in sodium homeostasis. SOS3 plays a critical role in plastic development of lateral roots through modulation of auxin gradients and maxima in roots under mild salt conditions. The SOS proteins also play a role in the dynamics of cytoskeleton under stress. These results imply a high complexity of the regulatory networks involved in plant response to salinity. This review focuses on the emerging complexity of the SOS signaling and SOS protein functions, and highlights recent understanding on how the SOS proteins contribute to different responses to salt stress besides ion homeostasis.

  13. [SOS-repair--60 years].

    Science.gov (United States)

    Zavil'gel'skiĭ, G B

    2013-01-01

    This review integrates 60 years of research on SOS-repair and SOS-mutagenesis in procaryotes and eucaryotes, from Jean Weigle experiment in 1953 year (mutagenesis of lambda bacteriophage in UV-irradiated bacteria) to the latest achievements in studying SOS-mutagenesis on all living organisms--Eukarya, Archaea and Bacteria. A key role in establishing of a biochemical basis for SOS-mutagenesis belonges to the finding in 1998-1999 years that specific error-prone DNA polymerases (PolV and others) catalysed translesion synthesis on damaged DNA. This review focuses on recent studies addressing the new models for SOS-induced mutagenesis in Escherichia coli and Home sapiens cells.

  14. NOAA NDBC SOS - waves

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NDBC SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have waves data. Because of the nature of SOS requests, requests for data...

  15. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Directory of Open Access Journals (Sweden)

    Haizhou Wu

    2016-01-01

    Full Text Available Symbiotic organisms search (SOS is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs. In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  16. Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

    Science.gov (United States)

    Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

    2017-10-06

    Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

  17. SOS: Observation, Intervention, and Scaffolding towards Successful Online Students

    Science.gov (United States)

    Ainsa, Trisha

    2017-01-01

    Research, reflection, and evaluation of online classes indicated a need for graduated scaffolding for first time students experiencing distance learning. In order to promote student engagement in the online learning process, I designed SOS for beginning online students. Sixty-three online students were offered an opportunity to participate in a…

  18. The Arabidopsis SOS2 protein kinase physically interacts with and is activated by the calcium-binding protein SOS3

    OpenAIRE

    Halfter, Ursula; Ishitani, Manabu; Zhu, Jian-Kang

    2000-01-01

    The Arabidopsis thaliana SOS2 and SOS3 genes are required for intracellular Na+ and K+ homeostasis and plant tolerance to high Na+ and low K+ environments. SOS3 is an EF hand type calcium-binding protein having sequence similarities with animal neuronal calcium sensors and the yeast calcineurin B. SOS2 is a serine/threonine protein kinase in the SNF1/AMPK family. We report here that SOS3 physically interacts with and activates SOS2 protein kinase. Genetically, sos2sos3 double mutant analysis ...

  19. Vesiculation from Pseudomonas aeruginosa under SOS.

    Science.gov (United States)

    Maredia, Reshma; Devineni, Navya; Lentz, Peter; Dallo, Shatha F; Yu, Jiehjuen; Guentzel, Neal; Chambers, James; Arulanandam, Bernard; Haskins, William E; Weitao, Tao

    2012-01-01

    Bacterial infections can be aggravated by antibiotic treatment that induces SOS response and vesiculation. This leads to a hypothesis concerning association of SOS with vesiculation. To test it, we conducted multiple analyses of outer membrane vesicles (OMVs) produced from the Pseudomonas aeruginosa wild type in which SOS is induced by ciprofloxacin and from the LexA noncleavable (lexAN) strain in which SOS is repressed. The levels of OMV proteins, lipids, and cytotoxicity increased for both the treated strains, demonstrating vesiculation stimulation by the antibiotic treatment. However, the further increase was suppressed in the lexAN strains, suggesting the SOS involvement. Obviously, the stimulated vesiculation is attributed by both SOS-related and unrelated factors. OMV subproteomic analysis was performed to examine these factors, which reflected the OMV-mediated cytotoxicity and the physiology of the vesiculating cells under treatment and SOS. Thus, SOS plays a role in the vesiculation stimulation that contributes to cytotoxicity.

  20. A Collaborative Education Network for Advancing Climate Literacy using Data Visualization Technology

    Science.gov (United States)

    McDougall, C.; Russell, E. L.; Murray, M.; Bendel, W. B.

    2013-12-01

    One of the more difficult issues in engaging broad audiences with scientific research is to present it in a way that is intuitive, captivating and up-to-date. Over the past ten years, the National Oceanic and Atmospheric Administration (NOAA) has made significant progress in this area through Science On a Sphere(R) (SOS). SOS is a room-sized, global display system that uses computers and video projectors to display Earth systems data onto a six-foot diameter sphere, analogous to a giant animated globe. This well-crafted data visualization system serves as a way to integrate and display global change phenomena; including polar ice melt, projected sea level rise, ocean acidification and global climate models. Beyond a display for individual data sets, SOS provides a holistic global perspective that highlights the interconnectedness of Earth systems, nations and communities. SOS is now a featured exhibit at more than 100 science centers, museums, universities, aquariums and other institutions around the world reaching more than 33 million visitors every year. To facilitate the development of how this data visualization technology and these visualizations could be used with public audiences, we recognized the need for the exchange of information among the users. To accomplish this, we established the SOS Users Collaborative Network. This network consists of the institutions that have an SOS system or partners who are creating content and educational programming for SOS. When we began the Network in 2005, many museums had limited capacity to both incorporate real-time, authentic scientific data about the Earth system and interpret global change visualizations. They needed not only the visualization platform and the scientific content, but also assistance with methods of approach. We needed feedback from these users on how to craft understandable visualizations and how to further develop the SOS platform to support learning. Through this Network and the collaboration

  1. NOAA NDBC SOS, 2007-present, currents

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NDBC SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have currents data. Because of the nature of SOS requests, requests for...

  2. NOAA NDBC SOS, 2006-present, winds

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NDBC SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have winds data. Because of the nature of SOS requests, requests for data...

  3. The investigation of SOS-response of Escherichia coli after γ-irradiation by means of SOS-chromotest

    International Nuclear Information System (INIS)

    Kozubek, S.; Ogievetskaya, M.M.; Krasavin, E.A.; Drasil, V.; Soska, J.

    1988-01-01

    The kinetics of the E.coli PQ37 SOS-system induction by γ-radiation has been studied by the SOS-chromotest technique. The experimental data are consistent with the following hypotheses. The production of DNA damages inducing the SOS-system is 0,021 Gy -1 per genome. The SOS-system is switched off approximately 200 min after γ-irradiation. The spontaneous triggering of the SOS-system is induced in the exponentially growing cells. The probability of its induction is independent of time up to 180 min of incubation. The synthesis of constitutive alkaline phosphatase proceeds for some time in the cells that suffered lethal damages from γ-irradiation. A correction has been proposed for the calculation of the induction factor. 5 refs.; 11 figs

  4. Ras activation by SOS

    DEFF Research Database (Denmark)

    Iversen, Lars; Tu, Hsiung-Lin; Lin, Wan-Chen

    2014-01-01

    Activation of the small guanosine triphosphatase H-Ras by the exchange factor Son of Sevenless (SOS) is an important hub for signal transduction. Multiple layers of regulation, through protein and membrane interactions, govern activity of SOS. We characterized the specific activity of individual ...

  5. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  6. The SOS response is permitted in Escherichia coli strains deficient in the expression of the mazEF pathway.

    Science.gov (United States)

    Kalderon, Ziva; Kumar, Sathish; Engelberg-Kulka, Hanna

    2014-01-01

    The Escherichia coli (E. coli) SOS response is the largest, most complex, and best characterized bacterial network induced by DNA damage. It is controlled by a complex network involving the RecA and LexA proteins. We have previously shown that the SOS response to DNA damage is inhibited by various elements involved in the expression of the E. coli toxin-antitoxin mazEF pathway. Since the mazEF module is present on the chromosomes of most E. coli strains, here we asked: Why is the SOS response found in so many E. coli strains? Is the mazEF module present but inactive in those strains? We examined three E. coli strains used for studies of the SOS response, strains AB1932, BW25113, and MG1655. We found that each of these strains is either missing or inhibiting one of several elements involved in the expression of the mazEF-mediated death pathway. Thus, the SOS response only takes place in E. coli cells in which one or more elements of the E. coli toxin-antitoxin module mazEF or its downstream pathway is not functioning.

  7. Systematically Altering Bacterial SOS Activity under Stress Reveals Therapeutic Strategies for Potentiating Antibiotics.

    Science.gov (United States)

    Mo, Charlie Y; Manning, Sara A; Roggiani, Manuela; Culyba, Matthew J; Samuels, Amanda N; Sniegowski, Paul D; Goulian, Mark; Kohli, Rahul M

    2016-01-01

    The bacterial SOS response is a DNA damage repair network that is strongly implicated in both survival and acquired drug resistance under antimicrobial stress. The two SOS regulators, LexA and RecA, have therefore emerged as potential targets for adjuvant therapies aimed at combating resistance, although many open questions remain. For example, it is not well understood whether SOS hyperactivation is a viable therapeutic approach or whether LexA or RecA is a better target. Furthermore, it is important to determine which antimicrobials could serve as the best treatment partners with SOS-targeting adjuvants. Here we derived Escherichia coli strains that have mutations in either lexA or recA genes in order to cover the full spectrum of possible SOS activity levels. We then systematically analyzed a wide range of antimicrobials by comparing the mean inhibitory concentrations (MICs) and induced mutation rates for each drug-strain combination. We first show that significant changes in MICs are largely confined to DNA-damaging antibiotics, with strains containing a constitutively repressed SOS response impacted to a greater extent than hyperactivated strains. Second, antibiotic-induced mutation rates were suppressed when SOS activity was reduced, and this trend was observed across a wider spectrum of antibiotics. Finally, perturbing either LexA or RecA proved to be equally viable strategies for targeting the SOS response. Our work provides support for multiple adjuvant strategies, while also suggesting that the combination of an SOS inhibitor with a DNA-damaging antibiotic could offer the best potential for lowering MICs and decreasing acquired drug resistance. IMPORTANCE Our antibiotic arsenal is becoming depleted, in part, because bacteria have the ability to rapidly adapt and acquire resistance to our best agents. The SOS pathway, a widely conserved DNA damage stress response in bacteria, is activated by many antibiotics and has been shown to play central role in

  8. A Modular SOS for Action Notation - Revisited

    DEFF Research Database (Denmark)

    Mosses, Peter David

    A draft modular SOS for the new version of AN, referred to as AN-2, has been available since 2000. It is written in CASL and has been checked for well-formedness using CATS (CASL Tool Set). It appears to be significantly more accessible than the original SOS of AN-1. However, it now appears......-notation for the modular SOS rules. After discussing the issues, we look at some illustrative examples taken from an improved modular SOS of AN-2 (in preparation). We also look at the possibility of empirical testing of the modular SOS by a straightforward translation to Prolog....

  9. SoS contract verification using statistical model checking

    Directory of Open Access Journals (Sweden)

    Alessandro Mignogna

    2013-11-01

    Full Text Available Exhaustive formal verification for systems of systems (SoS is impractical and cannot be applied on a large scale. In this paper we propose to use statistical model checking for efficient verification of SoS. We address three relevant aspects for systems of systems: 1 the model of the SoS, which includes stochastic aspects; 2 the formalization of the SoS requirements in the form of contracts; 3 the tool-chain to support statistical model checking for SoS. We adapt the SMC technique for application to heterogeneous SoS. We extend the UPDM/SysML specification language to express the SoS requirements that the implemented strategies over the SoS must satisfy. The requirements are specified with a new contract language specifically designed for SoS, targeting a high-level English- pattern language, but relying on an accurate semantics given by the standard temporal logics. The contracts are verified against the UPDM/SysML specification using the Statistical Model Checker (SMC PLASMA combined with the simulation engine DESYRE, which integrates heterogeneous behavioral models through the functional mock-up interface (FMI standard. The tool-chain allows computing an estimation of the satisfiability of the contracts by the SoS. The results help the system architect to trade-off different solutions to guide the evolution of the SoS.

  10. Sinusoidal obstruction syndrome (SOS) related to chemotherapy for colorectal liver metastases: factors predictive of severe SOS lesions and protective effect of bevacizumab.

    Science.gov (United States)

    Hubert, Catherine; Sempoux, Christine; Humblet, Yves; van den Eynde, Marc; Zech, Francis; Leclercq, Isabelle; Gigot, Jean-François

    2013-11-01

    The most frequent presentation of chemotherapy-related toxicity in colorectal liver metastases (CRLM) is sinusoidal obstruction syndrome (SOS). The purpose of the present study was to identify preoperative factors predictive of SOS and to establish associations between type of chemotherapy and severity of SOS. A retrospective study was carried out in a tertiary academic referral hospital. Patients suffering from CRLM who had undergone resection of at least one liver segment were included. Grading of SOS on the non-tumoral liver parenchyma was accomplished according to the Rubbia-Brandt criteria. A total of 151 patients were enrolled and divided into four groups according to the severity of SOS (grades 0-3). Multivariate analysis identified oxaliplatin and 5-fluorouracil as chemotherapeutic agents responsible for severe SOS lesions (P SOS lesions (P = 0.005). Univariate analysis identified the score on the aspartate aminotransferase : platelets ratio index (APRI) as the most significant biological factor predictive of severe SOS lesions. Splenomegaly is also significantly associated with the occurrence of severe SOS lesions. The APRI score and splenomegaly are effective as factors predictive of SOS. Bevacizumab has a protective effect against SOS. © 2013 International Hepato-Pancreato-Biliary Association.

  11. NOAA NOS SOS, EXPERIMENTAL - Currents

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have currents data. *These services are for testing and evaluation use...

  12. SOS System Induction Inhibits the Assembly of Chemoreceptor Signaling Clusters in Salmonella enterica.

    Science.gov (United States)

    Irazoki, Oihane; Mayola, Albert; Campoy, Susana; Barbé, Jordi

    2016-01-01

    Swarming, a flagellar-driven multicellular form of motility, is associated with bacterial virulence and increased antibiotic resistance. In this work we demonstrate that activation of the SOS response reversibly inhibits swarming motility by preventing the assembly of chemoreceptor-signaling polar arrays. We also show that an increase in the concentration of the RecA protein, generated by SOS system activation, rather than another function of this genetic network impairs chemoreceptor polar cluster formation. Our data provide evidence that the molecular balance between RecA and CheW proteins is crucial to allow polar cluster formation in Salmonella enterica cells. Thus, activation of the SOS response by the presence of a DNA-injuring compound increases the RecA concentration, thereby disturbing the equilibrium between RecA and CheW and resulting in the cessation of swarming. Nevertheless, when the DNA-damage decreases and the SOS response is no longer activated, basal RecA levels and thus polar cluster assembly are reestablished. These results clearly show that bacterial populations moving over surfaces make use of specific mechanisms to avoid contact with DNA-damaging compounds.

  13. NOAA NOS SOS, EXPERIMENTAL - Wind

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have wind data. *These services are for testing and evaluation use only*...

  14. The meaning of ordered SOS

    NARCIS (Netherlands)

    Mousavi, M.R.; Phillips, I.C.C.; Reniers, M.A.; Ulidowski, I.; Arun-Kumar, S.; Garg, N.

    2006-01-01

    Structured Operational Semantics (SOS) is a popular method for defining semantics by means of deduction rules. An important feature of deduction rules, or simply SOS rules, are negative premises, which are crucial in the definitions of such phenomena as priority mechanisms and time-outs. Orderings

  15. NOAA NDBC SOS, 2006-present, sea_water_temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NDBC SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have sea_water_temperature data. Because of the nature of SOS requests,...

  16. One-way membrane trafficking of SOS in receptor-triggered Ras activation.

    Science.gov (United States)

    Christensen, Sune M; Tu, Hsiung-Lin; Jun, Jesse E; Alvarez, Steven; Triplet, Meredith G; Iwig, Jeffrey S; Yadav, Kamlesh K; Bar-Sagi, Dafna; Roose, Jeroen P; Groves, Jay T

    2016-09-01

    SOS is a key activator of the small GTPase Ras. In cells, SOS-Ras signaling is thought to be initiated predominantly by membrane recruitment of SOS via the adaptor Grb2 and balanced by rapidly reversible Grb2-SOS binding kinetics. However, SOS has multiple protein and lipid interactions that provide linkage to the membrane. In reconstituted-membrane experiments, these Grb2-independent interactions were sufficient to retain human SOS on the membrane for many minutes, during which a single SOS molecule could processively activate thousands of Ras molecules. These observations raised questions concerning how receptors maintain control of SOS in cells and how membrane-recruited SOS is ultimately released. We addressed these questions in quantitative assays of reconstituted SOS-deficient chicken B-cell signaling systems combined with single-molecule measurements in supported membranes. These studies revealed an essentially one-way trafficking process in which membrane-recruited SOS remains trapped on the membrane and continuously activates Ras until being actively removed via endocytosis.

  17. Prototyping SOS meta-theory in Maude

    NARCIS (Netherlands)

    Mousavi, M.R.; Reniers, M.A.; Mosses, P.D.; Ulidowski, I.

    2006-01-01

    We present a prototype implementation of SOS meta-theory in the Maude term rewriting language. The prototype defines the basic concepts of SOS meta-theory (e.g., transition formulae, deduction rules and transition system specifications) in Maude. Besides the basic definitions, we implement methods

  18. Semantics and expressiveness of ordered SOS

    NARCIS (Netherlands)

    Mousavi, M.R.; Phillips, I.C.C.; Reniers, M.A.; Ulidowski, I.

    2009-01-01

    Structured Operational Semantics (SOS) is a popular method for defining semantics by means of transition rules. An important feature of SOS rules is negative premises, which are crucial in the definitions of such phenomena as priority mechanisms and time-outs. However, the inclusion of negative

  19. Absence of both Sos-1 and Sos-2 in peripheral CD4+ T cells leads to PI3K pathway activation and defects in migration

    Science.gov (United States)

    Guittard, Geoffrey; Kortum, Robert L; Balagopalan, Lakshmi; Çuburu, Nicolas; Nguyen, Phan; Sommers, Connie L; Samelson, Lawrence E

    2015-01-01

    Sos-1 and Sos-2 are ubiquitously expressed Ras-Guanine Exchange Factors involved in Erk-MAP kinase pathway activation. Using mice lacking genes encoding Sos-1 and Sos-2, we evaluated the role of these proteins in peripheral T-cell signaling and function. Our results confirmed that TCR-mediated Erk activation in peripheral CD4+ T cells does not depend on Sos-1 and Sos-2, although IL-2-mediated Erk activation does. Unexpectedly, however, we show an increase in AKT phosphorylation in Sos-1/2dKO CD4+ T cells upon TCR and IL-2 stimulation. Activation of AKT was likely a consequence of increased recruitment of PI3K to Grb2 upon TCR and/or IL-2 stimulation in Sos-1/2dKO CD4+ T cells. The increased activity of the PI3K/AKT pathway led to downregulation of the surface receptor CD62L in Sos-1/2dKO T cells and a subsequent impairment in T-cell migration. PMID:25973715

  20. Unexpected Cartilage Phenotype in CD4-Cre-Conditional SOS-Deficient Mice.

    Science.gov (United States)

    Guittard, Geoffrey; Gallardo, Devorah L; Li, Wenmei; Melis, Nicolas; Lui, Julian C; Kortum, Robert L; Shakarishvili, Nicholas G; Huh, Sunmee; Baron, Jeffrey; Weigert, Roberto; Kramer, Joshua A; Samelson, Lawrence E; Sommers, Connie L

    2017-01-01

    RAS signaling is central to many cellular processes and SOS proteins promote RAS activation. To investigate the role of SOS proteins in T cell biology, we crossed Sos1 f/f Sos2 -/- mice to CD4-Cre transgenic mice. We previously reported an effect of these mutations on T cell signaling and T cell migration. Unexpectedly, we observed nodules on the joints of greater than 90% of these mutant mice at 5 months of age, especially on the carpal joints. As the mice aged further, some also displayed joint stiffness, hind limb paralysis, and lameness. Histological analysis indicated that the abnormal growth in joints originated from dysplastic chondrocytes. Second harmonic generation imaging of the carpal nodules revealed that nodules were encased by rich collagen fibrous networks. Nodules formed in mice also deficient in RAG2, indicating that conventional T cells, which undergo rearrangement of the T cell antigen receptor, are not required for this phenotype. CD4-Cre expression in a subset of cells, either immune lineage cells (e.g., non-conventional T cells) or non-immune lineage cells (e.g., chondrocytes) likely mediates the dramatic phenotype observed in this study. Disruptions of genes in the RAS signaling pathway are especially likely to cause this phenotype. These results also serve as a cautionary tale to those intending to use CD4-Cre transgenic mice to specifically delete genes in conventional T cells.

  1. Ribonuclease E modulation of the bacterial SOS response.

    Directory of Open Access Journals (Sweden)

    Robert Manasherob

    Full Text Available Plants, animals, bacteria, and Archaea all have evolved mechanisms to cope with environmental or cellular stress. Bacterial cells respond to the stress of DNA damage by activation of the SOS response, the canonical RecA/LexA-dependent signal transduction pathway that transcriptionally derepresses a multiplicity of genes-leading to transient arrest of cell division and initiation of DNA repair. Here we report the previously unsuspected role of E. coli endoribonuclease RNase E in regulation of the SOS response. We show that RNase E deletion or inactivation of temperature-sensitive RNase E protein precludes normal initiation of SOS. The ability of RNase E to regulate SOS is dynamic, as down regulation of RNase E following DNA damage by mitomycin C resulted in SOS termination and restoration of RNase E function leads to resumption of a previously aborted response. Overexpression of the RraA protein, which binds to the C-terminal region of RNase E and modulates the actions of degradosomes, recapitulated the effects of RNase E deficiency. Possible mechanisms for RNase E effects on SOS are discussed.

  2. Ribonuclease E modulation of the bacterial SOS response.

    Science.gov (United States)

    Manasherob, Robert; Miller, Christine; Kim, Kwang-sun; Cohen, Stanley N

    2012-01-01

    Plants, animals, bacteria, and Archaea all have evolved mechanisms to cope with environmental or cellular stress. Bacterial cells respond to the stress of DNA damage by activation of the SOS response, the canonical RecA/LexA-dependent signal transduction pathway that transcriptionally derepresses a multiplicity of genes-leading to transient arrest of cell division and initiation of DNA repair. Here we report the previously unsuspected role of E. coli endoribonuclease RNase E in regulation of the SOS response. We show that RNase E deletion or inactivation of temperature-sensitive RNase E protein precludes normal initiation of SOS. The ability of RNase E to regulate SOS is dynamic, as down regulation of RNase E following DNA damage by mitomycin C resulted in SOS termination and restoration of RNase E function leads to resumption of a previously aborted response. Overexpression of the RraA protein, which binds to the C-terminal region of RNase E and modulates the actions of degradosomes, recapitulated the effects of RNase E deficiency. Possible mechanisms for RNase E effects on SOS are discussed.

  3. NOAA NDBC SOS, 2007-present, sea_water_practical_salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NDBC SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have sea_water_practical_salinity data. Because of the nature of SOS...

  4. Absence of both Sos-1 and Sos-2 in peripheral CD4(+) T cells leads to PI3K pathway activation and defects in migration.

    Science.gov (United States)

    Guittard, Geoffrey; Kortum, Robert L; Balagopalan, Lakshmi; Çuburu, Nicolas; Nguyen, Phan; Sommers, Connie L; Samelson, Lawrence E

    2015-08-01

    Sos-1 and Sos-2 are ubiquitously expressed Ras-guanine exchange factors involved in Erk-MAP kinase pathway activation. Using mice lacking genes encoding Sos-1 and Sos-2, we evaluated the role of these proteins in peripheral T-cell signaling and function. Our results confirmed that TCR-mediated Erk activation in peripheral CD4(+) T cells does not depend on Sos-1 and Sos-2, although IL-2-mediated Erk activation does. Unexpectedly, however, we show an increase in AKT phosphorylation in Sos-1/2dKO CD4(+) T cells upon TCR and IL-2 stimulation. Activation of AKT was likely a consequence of increased recruitment of PI3K to Grb2 upon TCR and/or IL-2 stimulation in Sos-1/2dKO CD4(+) T cells. The increased activity of the PI3K/AKT pathway led to downregulation of the surface receptor CD62L in Sos-1/2dKO T cells and a subsequent impairment in T-cell migration. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  5. Tolerance of Escherichia coli to fluoroquinolone antibiotics depends on specific components of the SOS response pathway.

    Science.gov (United States)

    Theodore, Alyssa; Lewis, Kim; Vulic, Marin

    2013-12-01

    Bacteria exposed to bactericidal fluoroquinolone (FQ) antibiotics can survive without becoming genetically resistant. Survival of these phenotypically resistant cells, commonly called "persisters," depends on the SOS gene network. We have examined mutants in all known SOS-regulated genes to identify functions essential for tolerance in Escherichia coli. The absence of DinG and UvrD helicases and the Holliday junction processing enzymes RuvA and RuvB leads to a decrease in survival. Analysis of the respective mutants indicates that, in addition to repair of double-strand breaks, tolerance depends on the repair of collapsed replication forks and stalled transcription complexes. Mutation in recF results in increased survival, which identifies RecAF recombination as a poisoning mechanism not previously linked to FQ lethality. DinG acts upstream of SOS promoting its induction, whereas RuvAB participates in repair only. UvrD directly promotes all repair processes initiated by FQ-induced damage and prevents RecAF-dependent misrepair, making it one of the crucial SOS functions required for tolerance.

  6. A Collaborative Learning Network Approach to Improvement: The CUSP Learning Network.

    Science.gov (United States)

    Weaver, Sallie J; Lofthus, Jennifer; Sawyer, Melinda; Greer, Lee; Opett, Kristin; Reynolds, Catherine; Wyskiel, Rhonda; Peditto, Stephanie; Pronovost, Peter J

    2015-04-01

    Collaborative improvement networks draw on the science of collaborative organizational learning and communities of practice to facilitate peer-to-peer learning, coaching, and local adaption. Although significant improvements in patient safety and quality have been achieved through collaborative methods, insight regarding how collaborative networks are used by members is needed. Improvement Strategy: The Comprehensive Unit-based Safety Program (CUSP) Learning Network is a multi-institutional collaborative network that is designed to facilitate peer-to-peer learning and coaching specifically related to CUSP. Member organizations implement all or part of the CUSP methodology to improve organizational safety culture, patient safety, and care quality. Qualitative case studies developed by participating members examine the impact of network participation across three levels of analysis (unit, hospital, health system). In addition, results of a satisfaction survey designed to evaluate member experiences were collected to inform network development. Common themes across case studies suggest that members found value in collaborative learning and sharing strategies across organizational boundaries related to a specific improvement strategy. The CUSP Learning Network is an example of network-based collaborative learning in action. Although this learning network focuses on a particular improvement methodology-CUSP-there is clear potential for member-driven learning networks to grow around other methods or topic areas. Such collaborative learning networks may offer a way to develop an infrastructure for longer-term support of improvement efforts and to more quickly diffuse creative sustainment strategies.

  7. Nominal SOS

    NARCIS (Netherlands)

    Cimini, M.; Mousavi, M.R.; Reniers, M.A.; Gabbay, M.J.

    2012-01-01

    Plotkin's style of Structural Operational Semantics (SOS) has become a de facto standard in giving operational semantics to formalisms and process calculi. In many such formalisms and calculi, the concepts of names, variables and binders are essential ingredients. In this paper, we propose a formal

  8. Inhibitors of Ras-SOS Interactions.

    Science.gov (United States)

    Lu, Shaoyong; Jang, Hyunbum; Zhang, Jian; Nussinov, Ruth

    2016-04-19

    Activating Ras mutations are found in about 30 % of human cancers. Ras activation is regulated by guanine nucleotide exchange factors, such as the son of sevenless (SOS), which form protein-protein interactions (PPIs) with Ras and catalyze the exchange of GDP by GTP. This is the rate-limiting step in Ras activation. However, Ras surfaces lack any evident suitable pockets where a molecule might bind tightly, rendering Ras proteins still 'undruggable' for over 30 years. Among the alternative approaches is the design of inhibitors that target the Ras-SOS PPI interface, a strategy that is gaining increasing recognition for treating Ras mutant cancers. Herein we focus on data that has accumulated over the past few years pertaining to the design of small-molecule modulators or peptide mimetics aimed at the interface of the Ras-SOS PPI. We emphasize, however, that even if such Ras-SOS therapeutics are potent, drug resistance may emerge. To counteract this development, we propose "pathway drug cocktails", that is, drug combinations aimed at parallel (or compensatory) pathways. A repertoire of classified cancer, cell/tissue, and pathway/protein combinations would be beneficial toward this goal. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Reconstitution in yeast of the Arabidopsis SOS signaling pathway for Na+ homeostasis

    OpenAIRE

    Quintero, Francisco J.; Ohta, Masaru; Shi, Huazhong; Zhu, Jian-Kang; Pardo, José M.

    2002-01-01

    The Arabidopsis thaliana SOS1 protein is a putative Na H antiporter that functions in Na extrusion and is essential for the NaCl tolerance of plants. sos1 mutant plants share phenotypic similarities with mutants lacking the protein kinase SOS2 and the Ca2 sensor SOS3. To investigate whether the three SOS proteins function in the same response pathway, we have reconstituted the SOS system in yeast cells. Expression of SOS1 improved the Na tolerance of yeast mutants la...

  10. Evelin Ilves avas SOS Lasteküla

    Index Scriptorium Estoniae

    2010-01-01

    SOS Lasteküla patroon proua Evelin Ilves avas 1. juunil 2010 Põltsamaal Eesti teise SOS Lasteküla. Presidendi abikaasa tõi kingiks õunapuuistikuid ja lasteraamatuid. Ilmunud ka: Eesti Päevaleht 2. juuni 2010, lk. 4

  11. NOAA NOS SOS, EXPERIMENTAL, 1902-present, Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have salinity data. *These services are for testing and evaluation use...

  12. NOAA NOS SOS, EXPERIMENTAL, 1902-present, Conductivity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have conductivity data. *These services are for testing and evaluation use...

  13. SOS! Ayuda para Padres: Una Guia Practica para Manejar Problemas de Conducta Comunes y Corrientes. (SOS! Help for Parents: A Practical Guide for Handling Common Everyday Behavior Problems.) Leader's Guide.

    Science.gov (United States)

    Clark, Lynn

    This Spanish-language version of "SOS" provides parents with guidance for handling a variety of common behavior problems based on the behavior approach to child rearing and discipline. This approach suggests that good and bad behavior are both learned and can be changed, and proposes specific methods, skills, procedures, and strategies…

  14. Redes de aprendizaje, aprendizaje en red Learning Networks, Networked Learning

    Directory of Open Access Journals (Sweden)

    Peter Sloep

    2011-10-01

    Full Text Available Las redes de aprendizaje (Learning Networks son redes sociales en línea mediante las cuales los participantes comparten información y colaboran para crear conocimiento. De esta manera, estas redes enriquecen la experiencia de aprendizaje en cualquier contexto de aprendizaje, ya sea de educación formal (en escuelas o universidades o educación no-formal (formación profesional. Aunque el concepto de aprendizaje en red suscita el interés de diferentes actores del ámbito educativo, aún existen muchos interrogantes sobre cómo debe diseñarse el aprendizaje en red para facilitar adecuadamente la educación y la formación. El artículo toma este interrogante como punto de partida, y posteriormente aborda cuestiones como la dinámica de la evolución de las redes de aprendizaje, la importancia de fomentar la confianza entre los participantes y el papel central que desempeña el perfil de usuario en la construcción de la confianza, así como el apoyo entre compañeros. Además, se elabora el proceso de diseño de una red de aprendizaje, y se describe un ejemplo en el contexto universitario. Basándonos en la investigación que actualmente se lleva a cabo en nuestro propio centro y en otros lugares, el capítulo concluye con una visión del futuro de las redes de aprendizaje.Learning Networks are on-line social networks through which users share knowledge with each other and jointly develop new knowledge. This way, Learning Networks may enrich the experience of formal, school-based learning and form a viable setting for professional development. Although networked learning enjoys an increasing interest, many questions remain on how exactly learning in such networked contexts can contribute to successful education and training. Put differently, how should networked learning be designed best to facilitate education and training? Taking this as its point of departure, the chapter addresses such issues as the dynamic evolution of Learning Networks

  15. Characterization of the Burkholderia thailandensis SOS response by using whole-transcriptome shotgun sequencing.

    Science.gov (United States)

    Ulrich, Ricky L; Deshazer, David; Kenny, Tara A; Ulrich, Melanie P; Moravusova, Anna; Opperman, Timothy; Bavari, Sina; Bowlin, Terry L; Moir, Donald T; Panchal, Rekha G

    2013-10-01

    The bacterial SOS response is a well-characterized regulatory network encoded by most prokaryotic bacterial species and is involved in DNA repair. In addition to nucleic acid repair, the SOS response is involved in pathogenicity, stress-induced mutagenesis, and the emergence and dissemination of antibiotic resistance. Using high-throughput sequencing technology (SOLiD RNA-Seq), we analyzed the Burkholderia thailandensis global SOS response to the fluoroquinolone antibiotic, ciprofloxacin (CIP), and the DNA-damaging chemical, mitomycin C (MMC). We demonstrate that a B. thailandensis recA mutant (RU0643) is ∼4-fold more sensitive to CIP in contrast to the parental strain B. thailandensis DW503. Our RNA-Seq results show that CIP and MMC treatment (P SOS response were induced and include lexA, uvrA, dnaE, dinB, recX, and recA. At the genome-wide level, we found an overall decrease in gene expression, especially for genes involved in amino acid and carbohydrate transport and metabolism, following both CIP and MMC exposure. Interestingly, we observed the upregulation of several genes involved in bacterial motility and enhanced transcription of a B. thailandensis genomic island encoding a Siphoviridae bacteriophage designated E264. Using B. thailandensis plaque assays and PCR with B. mallei ATCC 23344 as the host, we demonstrate that CIP and MMC exposure in B. thailandensis DW503 induces the transcription and translation of viable bacteriophage in a RecA-dependent manner. This is the first report of the SOS response in Burkholderia spp. to DNA-damaging agents. We have identified both common and unique adaptive responses of B. thailandensis to chemical stress and DNA damage.

  16. Bacterial SOS response: a food safety perspective

    NARCIS (Netherlands)

    Veen, van der S.; Abee, T.

    2011-01-01

    The SOS response is a conserved inducible pathway in bacteria that is involved in DNA repair and restart of stalled replication forks. Activation of the SOS response can result in stress resistance and mutagenesis. In food processing facilities and during food preservation, bacteria are exposed to

  17. SOS-projektet

    DEFF Research Database (Denmark)

    Blomhøj, Morten; Jensen, Tomas Højgaard

    2007-01-01

    Artiklen beretter om og analyserer det såkaldte SOS-projekt, hvor matematiklærere fra grundskolen, gymnasiet og læreruddannelsen har samarbejdet med matematikdidaktiske forskere om at undersøge og afhjælpe nogle af de udfordringer som danske elever møder i matematik ved overgangen fra grundskole...

  18. Motility of Pseudomonas aeruginosa contributes to SOS-inducible biofilm formation.

    Science.gov (United States)

    Chellappa, Shakinah T; Maredia, Reshma; Phipps, Kara; Haskins, William E; Weitao, Tao

    2013-12-01

    DNA-damaging antibiotics such as ciprofloxacin induce biofilm formation and the SOS response through autocleavage of SOS-repressor LexA in Pseudomonas aeruginosa. However, the biofilm-SOS connection remains poorly understood. It was investigated with 96-well and lipid biofilm assays. The effects of ciprofloxacin were examined on biofilm stimulation of the SOS mutant and wild-type strains. The stimulation observed in the wild-type in which SOS was induced was reduced in the mutant in which LexA was made non-cleavable (LexAN) and thus SOS non-inducible. Therefore, the stimulation appeared to involve SOS. The possible mechanisms of inducible biofilm formation were explored by subproteomic analysis of outer membrane fractions extracted from biofilms. The data predicted an inhibitory role of LexA in flagellum function. This premise was tested first by functional and morphological analyses of flagellum-based motility. The flagellum swimming motility decreased in the LexAN strain treated with ciprofloxacin. Second, the motility-biofilm assay was performed, which tested cell migration and biofilm formation. The results showed that wild-type biofilm increased significantly over the LexAN. These results suggest that LexA repression of motility, which is the initial event in biofilm development, contributes to repression of SOS-inducible biofilm formation. Copyright © 2013 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  19. Learning Analytics for Networked Learning Models

    Science.gov (United States)

    Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

    2014-01-01

    Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

  20. CMOS/SOS processing

    Science.gov (United States)

    Ramondetta, P.

    1980-01-01

    Report describes processes used in making complementary - metal - oxide - semiconductor/silicon-on-sapphire (CMOS/SOS) integrated circuits. Report lists processing steps ranging from initial preparation of sapphire wafers to final mapping of "good" and "bad" circuits on a wafer.

  1. Phosphotyrosine-mediated LAT assembly on membranes drives kinetic bifurcation in recruitment dynamics of the Ras activator SOS.

    Science.gov (United States)

    Huang, William Y C; Yan, Qingrong; Lin, Wan-Chen; Chung, Jean K; Hansen, Scott D; Christensen, Sune M; Tu, Hsiung-Lin; Kuriyan, John; Groves, Jay T

    2016-07-19

    The assembly of cell surface receptors with downstream signaling molecules is a commonly occurring theme in multiple signaling systems. However, little is known about how these assemblies modulate reaction kinetics and the ultimate propagation of signals. Here, we reconstitute phosphotyrosine-mediated assembly of extended linker for the activation of T cells (LAT):growth factor receptor-bound protein 2 (Grb2):Son of Sevenless (SOS) networks, derived from the T-cell receptor signaling system, on supported membranes. Single-molecule dwell time distributions reveal two, well-differentiated kinetic species for both Grb2 and SOS on the LAT assemblies. The majority fraction of membrane-recruited Grb2 and SOS both exhibit fast kinetics and single exponential dwell time distributions, with average dwell times of hundreds of milliseconds. The minor fraction exhibits much slower kinetics, extending the dwell times to tens of seconds. Considering this result in the context of the multistep process by which the Ras GEF (guanine nucleotide exchange factor) activity of SOS is activated indicates that kinetic stabilization from the LAT assembly may be important. This kinetic proofreading effect would additionally serve as a stochastic noise filter by reducing the relative probability of spontaneous SOS activation in the absence of receptor triggering. The generality of receptor-mediated assembly suggests that such effects may play a role in multiple receptor proximal signaling processes.

  2. NOAA NOS SOS, EXPERIMENTAL, 1853-present, Barometric Pressure

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have barometric pressure data. *These services are for testing and...

  3. Mathematical model of the SOS response regulation in wild-type Escherichia coli

    International Nuclear Information System (INIS)

    Aksenov, S.V.

    1997-01-01

    Regulation of the SOS response in Escherichia coli, which is a set of inducible cellular reactions introduced after DNA damage, is due to specific interaction of LexA and RecA proteins. LexA protein is a common repressor of the genes of the SOS system, and RecA protein, once transiently activated by the so-called SOS-inducing signal, promotes LexA protein destruction. We have described the SOS regulation by means of differential equations with regard to LexA and RecA concentrations elsewhere. The 'input' function for model equations is the level of the SOS-inducing signal against time. Here we present a means for calculating the concentration of single-stranded DNA (SOS-inducing signal) as a function of time in wild-type cells after ultraviolet irradiation. With model equations one can simulate kinetic curves of SOS regulatory proteins after DNA damage to survey the SOS response kinetics. Simulation of LexA protein kinetics agrees with experimental data. We compare simulated LexA kinetic curves in wild-type and uνr - mutant bacteria, which is useful in investigating the way uνrABC-dependent excision repair modulates the SOS response kinetics. Possible applications of the model to investigating various aspects of the SOS induction are discussed

  4. Quinolone Resistance Reversion by Targeting the SOS Response.

    Science.gov (United States)

    Recacha, E; Machuca, J; Díaz de Alba, P; Ramos-Güelfo, M; Docobo-Pérez, F; Rodriguez-Beltrán, J; Blázquez, J; Pascual, A; Rodríguez-Martínez, J M

    2017-10-10

    Suppression of the SOS response has been postulated as a therapeutic strategy for potentiating antimicrobial agents. We aimed to evaluate the impact of its suppression on reversing resistance using a model of isogenic strains of Escherichia coli representing multiple levels of quinolone resistance. E. coli mutants exhibiting a spectrum of SOS activity were constructed from isogenic strains carrying quinolone resistance mechanisms with susceptible and resistant phenotypes. Changes in susceptibility were evaluated by static (MICs) and dynamic (killing curves or flow cytometry) methodologies. A peritoneal sepsis murine model was used to evaluate in vivo impact. Suppression of the SOS response was capable of resensitizing mutant strains with genes encoding three or four different resistance mechanisms (up to 15-fold reductions in MICs). Killing curve assays showed a clear disadvantage for survival (Δlog 10 CFU per milliliter [CFU/ml] of 8 log units after 24 h), and the in vivo efficacy of ciprofloxacin was significantly enhanced (Δlog 10 CFU/g of 1.76 log units) in resistant strains with a suppressed SOS response. This effect was evident even after short periods (60 min) of exposure. Suppression of the SOS response reverses antimicrobial resistance across a range of E. coli phenotypes from reduced susceptibility to highly resistant, playing a significant role in increasing the in vivo efficacy. IMPORTANCE The rapid rise of antibiotic resistance in bacterial pathogens is now considered a major global health crisis. New strategies are needed to block the development of resistance and to extend the life of antibiotics. The SOS response is a promising target for developing therapeutics to reduce the acquisition of antibiotic resistance and enhance the bactericidal activity of antimicrobial agents such as quinolones. Significant questions remain regarding its impact as a strategy for the reversion or resensitization of antibiotic-resistant bacteria. To address this

  5. NOAA NOS SOS, EXPERIMENTAL, 1853-present, Air Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have air temperature data. *These services are for testing and evaluation...

  6. NOAA NOS SOS, EXPERIMENTAL, 1853-present, Water Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have water temperature data. *These services are for testing and evaluation...

  7. Theoretical model of the SOS effect

    Energy Technology Data Exchange (ETDEWEB)

    Darznek, S A; Mesyats, G A; Rukin, S N; Tsiranov, S N [Russian Academy of Sciences, Ural Division, Ekaterinburg (Russian Federation). Institute of Electrophysics

    1997-12-31

    Physical principles underlying the operation of semiconductor opening switches (SOS) are highlighted. The SOS effect occurs at a current density of up to 60 kA/cm{sup 2} in silicon p{sup +}-p-n-n{sup +} structures filled with residual electron-hole plasma. Using a theoretical model developed for plasma dynamic calculations, the mechanism by which current passes through the structure at the stage of high conduction and the processes that take place at the stage of current interruption were analyzed. The dynamics of the processes taking place in the structure was calculated with allowance for both diffusive and drift mechanisms of carrier transport. In addition, two recombination types, viz. recombination via impurities and impact Auger recombination, were included in the model. The effect of the structure on the pumping-circuit current and voltage was also taken into account. The real distribution of the doped impurity in the structure and the avalanche mechanism of carrier multiplication were considered. The results of calculations of a typical SOS are presented. The dynamics of the electron-hole plasma is analyzed. It is shown that the SOS effect represents a qualitatively new mechanism of current interruption in semiconductor structures. (author). 4 figs., 7 refs.

  8. The complex between SOS3 and SOS2 regulatory domain from Arabidopsis thaliana: cloning, expression, purification, crystallization and preliminary X-ray analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sánchez-Barrena, María José; Moreno-Pérez, Sandra; Angulo, Iván; Martínez-Ripoll, Martín; Albert, Armando, E-mail: xalbert@iqfr.csic.es [Grupo de Cristalografía Macromolecular y Biología Estructural, Instituto de Química Física ‘Rocasolano’, Consejo Superior de Investigaciones Científicas, Serrano 119, E-28006 Madrid (Spain)

    2007-07-01

    Recombinant SOS3 and SOS2 regulatory domain from A. thaliana have been coexpressed in E. coli, purified and crystallized by the hanging-drop vapour-diffusion method. An X-ray data set has been collected at 2.0 Å resolution. The salt-tolerance genes SOS3 (salt overly sensitive 3) and SOS2 (salt overly sensitive 2) regulatory domain of Arabidopsis thaliana were cloned into a polycistronic plasmid and the protein complex was expressed in Escherichia coli, allowing purification to homogeneity in three chromatographic steps. Crystals were grown using vapour-diffusion techniques. The crystals belonged to space group P2{sub 1}2{sub 1}2{sub 1}, with unit-cell parameters a = 44.14, b = 57.39, c = 141.90 Å.

  9. The Verrucomicrobia LexA-binding Motif: Insights into the Evolutionary Dynamics of the SOS Response

    Directory of Open Access Journals (Sweden)

    Ivan Erill

    2016-07-01

    Full Text Available The SOS response is the primary bacterial mechanism to address DNA damage, coordinating multiple cellular processes that include DNA repair, cell division and translesion synthesis. In contrast to other regulatory systems, the composition of the SOS genetic network and the binding motif of its transcriptional repressor, LexA, have been shown to vary greatly across bacterial clades, making it an ideal system to study the co-evolution of transcription factors and their regulons. Leveraging comparative genomics approaches and prior knowledge on the core SOS regulon, here we define the binding motif of the Verrucomicrobia, a recently described phylum of emerging interest due to its association with eukaryotic hosts. Site directed mutagenesis of the Verrucomicrobium spinosum recA promoter confirms that LexA binds a 14 bp palindromic motif with consensus sequence TGTTC-N4-GAACA. Computational analyses suggest that recognition of this novel motif is determined primarily by changes in base-contacting residues of the third alpha helix of the LexA helix-turn-helix DNA binding motif. In conjunction with comparative genomics analysis of the LexA regulon in the Verrucomicrobia phylum, electrophoretic shift assays reveal that LexA binds to operators in the promoter region of DNA repair genes and a mutagenesis cassette in this organism, and identify previously unreported components of the SOS response. The identification of tandem LexA-binding sites generating instances of other LexA-binding motifs in the lexA gene promoter of Verrucomicrobia species leads us to postulate a novel mechanism for LexA-binding motif evolution. This model, based on gene duplication, successfully addresses outstanding questions in the intricate co-evolution of the LexA protein, its binding motif and the regulatory network it controls.

  10. The Verrucomicrobia LexA-Binding Motif: Insights into the Evolutionary Dynamics of the SOS Response.

    Science.gov (United States)

    Erill, Ivan; Campoy, Susana; Kılıç, Sefa; Barbé, Jordi

    2016-01-01

    The SOS response is the primary bacterial mechanism to address DNA damage, coordinating multiple cellular processes that include DNA repair, cell division, and translesion synthesis. In contrast to other regulatory systems, the composition of the SOS genetic network and the binding motif of its transcriptional repressor, LexA, have been shown to vary greatly across bacterial clades, making it an ideal system to study the co-evolution of transcription factors and their regulons. Leveraging comparative genomics approaches and prior knowledge on the core SOS regulon, here we define the binding motif of the Verrucomicrobia, a recently described phylum of emerging interest due to its association with eukaryotic hosts. Site directed mutagenesis of the Verrucomicrobium spinosum recA promoter confirms that LexA binds a 14 bp palindromic motif with consensus sequence TGTTC-N4-GAACA. Computational analyses suggest that recognition of this novel motif is determined primarily by changes in base-contacting residues of the third alpha helix of the LexA helix-turn-helix DNA binding motif. In conjunction with comparative genomics analysis of the LexA regulon in the Verrucomicrobia phylum, electrophoretic shift assays reveal that LexA binds to operators in the promoter region of DNA repair genes and a mutagenesis cassette in this organism, and identify previously unreported components of the SOS response. The identification of tandem LexA-binding sites generating instances of other LexA-binding motifs in the lexA gene promoter of Verrucomicrobia species leads us to postulate a novel mechanism for LexA-binding motif evolution. This model, based on gene duplication, successfully addresses outstanding questions in the intricate co-evolution of the LexA protein, its binding motif and the regulatory network it controls.

  11. NOAA NOS SOS, EXPERIMENTAL, 1853-present, Water Level

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NOS SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have water surface height above a reference datum. *These services are for...

  12. Learning Networks for Lifelong Learning

    OpenAIRE

    Sloep, Peter

    2009-01-01

    Presentation in a seminar organized by Christopher Hoadley at Penn State University, October 2004.Contains general introduction into the Learning Network Programme and a demonstration of the Netlogo Simulation of a Learning Network.

  13. NOAA NDBC SOS, 2008-present, sea_floor_depth_below_sea_surface

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA NDBC SOS server is part of the IOOS DIF SOS Project. The stations in this dataset have sea_floor_depth_below_sea_surface data. Because of the nature of SOS...

  14. Ras activation by SOS: Allosteric regulation by altered fluctuation dynamics

    Science.gov (United States)

    Iversen, Lars; Tu, Hsiung-Lin; Lin, Wan-Chen; Christensen, Sune M.; Abel, Steven M.; Iwig, Jeff; Wu, Hung-Jen; Gureasko, Jodi; Rhodes, Christopher; Petit, Rebecca S.; Hansen, Scott D.; Thill, Peter; Yu, Cheng-Han; Stamou, Dimitrios; Chakraborty, Arup K.; Kuriyan, John; Groves, Jay T.

    2014-01-01

    Activation of the small guanosine triphosphatase H-Ras by the exchange factor Son of Sevenless (SOS) is an important hub for signal transduction. Multiple layers of regulation, through protein and membrane interactions, govern activity of SOS. We characterized the specific activity of individual SOS molecules catalyzing nucleotide exchange in H-Ras. Single-molecule kinetic traces revealed that SOS samples a broad distribution of turnover rates through stochastic fluctuations between distinct, long-lived (more than 100 seconds), functional states. The expected allosteric activation of SOS by Ras–guanosine triphosphate (GTP) was conspicuously absent in the mean rate. However, fluctuations into highly active states were modulated by Ras-GTP. This reveals a mechanism in which functional output may be determined by the dynamical spectrum of rates sampled by a small number of enzymes, rather than the ensemble average. PMID:24994643

  15. Adaptive symbiotic organisms search (SOS algorithm for structural design optimization

    Directory of Open Access Journals (Sweden)

    Ghanshyam G. Tejani

    2016-07-01

    Full Text Available The symbiotic organisms search (SOS algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.

  16. Mapping Modular SOS to Rewriting Logic

    DEFF Research Database (Denmark)

    Braga, Christiano de Oliveira; Haeusler, Erik Hermann; Meseguer, José

    Modular SOS (MSOS) is a framework created to improve the modularity of structural operational semantics specifications, a formalism frequently used in the fields of programming languages semantics and process algebras. With the objective of defining formal tools to support the execution and verif......Modular SOS (MSOS) is a framework created to improve the modularity of structural operational semantics specifications, a formalism frequently used in the fields of programming languages semantics and process algebras. With the objective of defining formal tools to support the execution...

  17. Mapping Modular SOS to Rewriting Logic

    DEFF Research Database (Denmark)

    Braga, Christiano de Oliveira; Haeusler, Edward Hermann; Meseguer, José

    2003-01-01

    Modular SOS (MSOS) is a framework created to improve the modularity of structural operational semantics specifications, a formalism frequently used in the fields of programming languages semantics and process algebras. With the objective of defining formal tools to support the execution and verif......Modular SOS (MSOS) is a framework created to improve the modularity of structural operational semantics specifications, a formalism frequently used in the fields of programming languages semantics and process algebras. With the objective of defining formal tools to support the execution...

  18. Quinolone Resistance Reversion by Targeting the SOS Response

    Directory of Open Access Journals (Sweden)

    E. Recacha

    2017-10-01

    Full Text Available Suppression of the SOS response has been postulated as a therapeutic strategy for potentiating antimicrobial agents. We aimed to evaluate the impact of its suppression on reversing resistance using a model of isogenic strains of Escherichia coli representing multiple levels of quinolone resistance. E. coli mutants exhibiting a spectrum of SOS activity were constructed from isogenic strains carrying quinolone resistance mechanisms with susceptible and resistant phenotypes. Changes in susceptibility were evaluated by static (MICs and dynamic (killing curves or flow cytometry methodologies. A peritoneal sepsis murine model was used to evaluate in vivo impact. Suppression of the SOS response was capable of resensitizing mutant strains with genes encoding three or four different resistance mechanisms (up to 15-fold reductions in MICs. Killing curve assays showed a clear disadvantage for survival (Δlog10 CFU per milliliter [CFU/ml] of 8 log units after 24 h, and the in vivo efficacy of ciprofloxacin was significantly enhanced (Δlog10 CFU/g of 1.76 log units in resistant strains with a suppressed SOS response. This effect was evident even after short periods (60 min of exposure. Suppression of the SOS response reverses antimicrobial resistance across a range of E. coli phenotypes from reduced susceptibility to highly resistant, playing a significant role in increasing the in vivo efficacy.

  19. SOS - Der kaldes på Smartere Offentlig Styring

    DEFF Research Database (Denmark)

    Hjortdal, Henrik

    2017-01-01

    Smartere Offentlig Styring eller SOS. Det var temaet da over hundrede kommunale direktører drøftede offentlig ledelse med en lang række toneangivende danske forskere.......Smartere Offentlig Styring eller SOS. Det var temaet da over hundrede kommunale direktører drøftede offentlig ledelse med en lang række toneangivende danske forskere....

  20. Mutational specificity of SOS mutagenesis

    International Nuclear Information System (INIS)

    Kato, Takeshi

    1986-01-01

    In an approach to the isolation of mutants of E. coli unable to produce mutations by ultraviolet light, the author has found new umuC-mutants. Their properties could be explained by ''SOS hypothesis of Radman and Witkin'', which has now been justified by many investigators. Analysis of the umuC region of E. coli chromosome cloned in pSK 100 has led to the conclusion that two genes, umuD and umuC, having the capacity of mutation induction express in the same mechanism as that of SOS genes, which is known to be inhibited by LexA protein bonding to ''SOS box'' found at promotor region. Suppressor analysis for mutational specificity has revealed: (i) umuDC-independent mutagens, such as EMS and (oh) 4 Cy, induce selected base substitution alone; and (ii) umuDC-dependent mutagens, such as X-rays and gamma-rays, induce various types of base substitution simultaneously, although they have mutational specificity. In the umuDC-dependent processes of basechange mutagenesis, the spectra of base substitution were a mixture of base substitution reflecting the specific base damages induced by individual mutagens and nonspecific base substitution. In conclusion, base substitution plays the most important role in umuDC-dependent mutagenesis, although mutagenesis of umuDC proteins remains uncertain. (Namekawa, K.)

  1. Research, Boundaries, and Policy in Networked Learning

    DEFF Research Database (Denmark)

    This book presents cutting-edge, peer reviewed research on networked learning organized by three themes: policy in networked learning, researching networked learning, and boundaries in networked learning. The "policy in networked learning" section explores networked learning in relation to policy...... networks, spaces of algorithmic governance and more. The "boundaries in networked learning" section investigates frameworks of students' digital literacy practices, among other important frameworks in digital learning. Lastly, the "research in networked learning" section delves into new research methods...

  2. Advances/applications of MAGIC and SOS

    Science.gov (United States)

    Warren, Gary; Ludeking, Larry; Nguyen, Khanh; Smithe, David; Goplen, Bruce

    1993-12-01

    MAGIC and SOS have been applied to investigate a variety of accelerator-related devices. Examples include high brightness electron guns, beam-RF interactions in klystrons, cold-test modes in an RFQ and in RF sources, and a high-quality, flexible, electron gun with operating modes appropriate for gyrotrons, peniotrons, and other RF sources. Algorithmic improvements for PIC have been developed and added to MAGIC and SOS to facilitate these modeling efforts. Two new field algorithms allow improved control of computational numerical noise and selective control of harmonic modes in RF cavities. An axial filter in SOS accelerates simulations in cylindrical coordinates. The recent addition of an export/import feature now allows long devices to be modeled in sections. Interfaces have been added to receive electromagnetic field information from the Poisson group of codes and from EGUN and to send beam information to PARMELA for subsequent tracing of bunches through beam optics. Post-processors compute and display beam properties including geometric, normalized, and slice emittances, and phase-space parameters, and video. VMS, UNIX, and DOS versions are supported, with migration underway toward windows environments.

  3. Thymineless death is inhibited by CsrA in Escherichia coli lacking the SOS response.

    Science.gov (United States)

    Hamilton, Holly M; Wilson, Ray; Blythe, Martin; Nehring, Ralf B; Fonville, Natalie C; Louis, Edward J; Rosenberg, Susan M

    2013-11-01

    Thymineless death (TLD) is the rapid loss of colony-forming ability in bacterial, yeast and human cells starved for thymine, and is the mechanism of action of common chemotherapeutic drugs. In Escherichia coli, significant loss of viability during TLD requires the SOS replication-stress/DNA-damage response, specifically its role in inducing the inhibitor of cell division, SulA. An independent RecQ- and RecJ-dependent TLD pathway accounts for a similarly large additional component of TLD, and a third SOS- and RecQ/J-independent TLD pathway has also been observed. Although two groups have implicated the SOS-response in TLD, an SOS-deficient mutant strain from an earlier study was found to be sensitive to thymine deprivation. We performed whole-genome resequencing on that SOS-deficient strain and find that, compared with the SOS-proficient control strain, it contains five mutations in addition to the SOS-blocking lexA(Ind(-)) mutation. One of the additional mutations, csrA, confers TLD sensitivity specifically in SOS-defective strains. We find that CsrA, a carbon storage regulator, reduces TLD in SOS- or SulA-defective cells, and that the increased TLD that occurs in csrA(-) SOS-defective cells is dependent on RecQ. We consider a hypothesis in which the modulation of nucleotide pools by CsrA might inhibit TLD specifically in SOS-deficient (SulA-deficient) cells. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Lastekaitsepäeval avati Põltsamaal SOS-peremajad / Raivo Feldmann

    Index Scriptorium Estoniae

    Feldmann, Raivo

    2010-01-01

    Eesti teise SOS Lasteküla ametlikul avamisel Põltsamaal 1. juunil 2010. a. osalesid ka Norra suursaadik Eestis Stein Vegard Hagen ja SOS Lasteküla patroon proua Evelin Ilves. Presidendi abikaasa kinkis igale perele pereõunapuu ja koos kirjastusega Varrak igale peremajale väikese koduraamatukogu

  5. Conditions for Productive Learning in Network Learning Environments

    DEFF Research Database (Denmark)

    Ponti, M.; Dirckinck-Holmfeld, Lone; Lindström, B.

    2004-01-01

    are designed without a deep understanding of the pedagogical, communicative and collaborative conditions embedded in networked learning. Despite the existence of good theoretical views pointing to a social understanding of learning, rather than a traditional individualistic and information processing approach......The Kaleidoscope1 Jointly Executed Integrating Research Project (JEIRP) on Conditions for Productive Networked Learning Environments is developing and elaborating conceptual understandings of Computer Supported Collaborative Learning (CSCL) emphasizing the use of cross-cultural comparative......: Pedagogical design and the dialectics of the digital artefacts, the concept of collaboration, ethics/trust, identity and the role of scaffolding of networked learning environments.   The JEIRP is motivated by the fact that many networked learning environments in various European educational settings...

  6. Suppression of the E. coli SOS response by dNTP pool changes.

    Science.gov (United States)

    Maslowska, Katarzyna H; Makiela-Dzbenska, Karolina; Fijalkowska, Iwona J; Schaaper, Roel M

    2015-04-30

    The Escherichia coli SOS system is a well-established model for the cellular response to DNA damage. Control of SOS depends largely on the RecA protein. When RecA is activated by single-stranded DNA in the presence of a nucleotide triphosphate cofactor, it mediates cleavage of the LexA repressor, leading to expression of the 30(+)-member SOS regulon. RecA activation generally requires the introduction of DNA damage. However, certain recA mutants, like recA730, bypass this requirement and display constitutive SOS expression as well as a spontaneous (SOS) mutator effect. Presently, we investigated the possible interaction between SOS and the cellular deoxynucleoside triphosphate (dNTP) pools. We found that dNTP pool changes caused by deficiencies in the ndk or dcd genes, encoding nucleoside diphosphate kinase and dCTP deaminase, respectively, had a strongly suppressive effect on constitutive SOS expression in recA730 strains. The suppression of the recA730 mutator effect was alleviated in a lexA-deficient background. Overall, the findings suggest a model in which the dNTP alterations in the ndk and dcd strains interfere with the activation of RecA, thereby preventing LexA cleavage and SOS induction. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  7. Learning Networks for Professional Development & Lifelong Learning

    NARCIS (Netherlands)

    Brouns, Francis; Sloep, Peter

    2009-01-01

    Brouns, F., & Sloep, P. B. (2009). Learning Networks for Professional Development & Lifelong Learning. Presentation of the Learning Network Programme for a Korean delegation of Chonnam National University and Dankook University (researchers dr. Jeeheon Ryu and dr. Minjeong Kim and a Group of PhD and

  8. Network Learning and Innovation in SME Formal Networks

    Directory of Open Access Journals (Sweden)

    Jivka Deiters

    2013-02-01

    Full Text Available The driver for this paper is the need to better understand the potential for learning and innovation that networks canprovide especially for small and medium sized enterprises (SMEs which comprise by far the majority of enterprises in the food sector. With the challenges the food sector is facing in the near future, learning and innovation or more focused, as it is being discussed in the paper, ‘learning for innovation’ are not just opportunities but pre‐conditions for the sustainability of the sector. Network initiatives that could provide appropriate support involve social interaction and knowledge exchange, learning, competence development, and coordination (organization and management of implementation. The analysis identifies case studies in any of these orientations which serve different stages of the innovation process: invention and implementation. The variety of network case studies cover networks linked to a focus group for training, research, orconsulting, networks dealing with focused market oriented product or process development, promotional networks, and networks for open exchange and social networking.

  9. Factors limiting SOS expression in log-phase cells of Escherichia coli.

    Science.gov (United States)

    Massoni, Shawn C; Leeson, Michael C; Long, Jarukit Edward; Gemme, Kristin; Mui, Alice; Sandler, Steven J

    2012-10-01

    In Escherichia coli, RecA-single-stranded DNA (RecA-ssDNA) filaments catalyze DNA repair, recombination, and induction of the SOS response. It has been shown that, while many (15 to 25%) log-phase cells have RecA filaments, few (about 1%) are induced for SOS. It is hypothesized that RecA's ability to induce SOS expression in log-phase cells is repressed because of the potentially detrimental effects of SOS mutagenesis. To test this, mutations were sought to produce a population where the number of cells with SOS expression more closely equaled the number of RecA filaments. Here, it is shown that deleting radA (important for resolution of recombination structures) and increasing recA transcription 2- to 3-fold with a recAo1403 operator mutation act independently to minimally satisfy this condition. This allows 24% of mutant cells to have elevated levels of SOS expression, a percentage similar to that of cells with RecA-green fluorescent protein (RecA-GFP) foci. In an xthA (exonuclease III gene) mutant where there are 3-fold more RecA loading events, recX (a destabilizer of RecA filaments) must be additionally deleted to achieve a population of cells where the percentage having elevated SOS expression (91%) nearly equals the percentage with at least one RecA-GFP focus (83%). It is proposed that, in the xthA mutant, there are three independent mechanisms that repress SOS expression in log-phase cells. These are the rapid processing of RecA filaments by RadA, maintaining the concentration of RecA below a critical level, and the destabilizing of RecA filaments by RecX. Only the first two mechanisms operate independently in a wild-type cell.

  10. Construct Validity of the Societal Outreach Scale (SOS).

    Science.gov (United States)

    Fike, David S; Denton, Jason; Walk, Matt; Kish, Jennifer; Gorman, Ira

    2018-04-01

    The American Physical Therapy Association (APTA) has been working toward a vision of increasing professional focus on societal-level health. However, performance of social responsibility and related behaviors by physical therapists remain relatively poorly integrated into practice. Promoting a focus on societal outreach is necessary for all health care professionals to impact the health of their communities. The objective was to document the validity of the 14-item Societal Outreach Scale (SOS) for use with practicing physical therapists. This study used a cross-sectional survey. The SOS was transmitted via email to all therapists who were licensed and practicing in 10 states in the United States that were purposefully selected to assure a broad representation. A sample of 2612 usable responses was received. Factor analysis was applied to assess construct validity of the instrument. Of alternate models, a 3-factor model best demonstrated goodness of fit with the sample data according to conventional indices (standardized root mean squared residual = .03, comparative fit index .96, root mean square error of approximation = .06). The 3 factors measured by the SOS were labeled Societal-Level Health Advocacy, Community Engagement/Social Integration, and Political Engagement. Internal consistency reliability was 0.7 for all factors. The 3-factor SOS demonstrated acceptable validity and reliability. Though the sample included a broad representation of physical therapists, this was a single cross-sectional study. Additional confirmatory factor analysis, reliability testing, and word refinement of the tool are warranted. Given the construct validity and reliability of the 3-factor SOS, it is recommended for use as a validated instrument to measure physical therapists' performance of social responsibility and related behaviors.

  11. Bevacizumab exacerbates sinusoidal obstruction syndrome (SOS) in the animal model and increases MMP 9 production.

    Science.gov (United States)

    Jafari, Azin; Matthaei, Hanno; Wehner, Sven; Tonguc, Tolga; Kalff, Jörg C; Manekeller, Steffen

    2018-04-24

    Thanks to modern multimodal treatment the ouctome of patients with colorectal cancer has experienced significant improvements. As a downside, agent specific side effects have been observed such as sinusoidal obstruction syndrome (SOS) after oxaliplatin chemotherapy (OX). Bevazicumab targeting VEGF is nowadays comprehensively used in combination protocols with OX but its impact on hepatotoxicity is thus far elusive and focus of the present study. After MCT administration 67% of animals developed SOS. GOT serum concentration significantly increased in animals developing SOS ( p SOS. In contrast, animals receiving VEGF developed SOS merely in 40% while increasing the VEGF dose led to a further decrease in SOS development to 25%. MMP 9 concentration in animals developing SOS was significantly higher compared to controls ( p SOS paralleled by MMP 9 production. Therefore, OX-Bevacizumab combination therapies should be administered with caution, especially if liver parenchyma damage is apparent. Male Sprague-Dawley rats were gavaged Monocrotaline (MCT) to induce SOS. Recombinant VEGF or an Anti-VEGF antibody was administered to MCT-treated rats and the hepatotoxic effect monitored in defined time intervals. MMP 9 expression in the liver was measured by ELISA.

  12. A flow cytometry-optimized assay using an SOS-green fluorescent protein (SOS-GFP) whole-cell biosensor for the detection of genotoxins in complex environments

    DEFF Research Database (Denmark)

    Norman, Anders; Hansen, Lars H.; Sørensen, Søren Johannes

    2006-01-01

    /mL, and proved far more sensitive than a previously published assay using the same biosensor strain. By applying the SOS-green fluorescent protein (GFP) whole-cell biosensor directly to soil microcosms we were also able to evaluate both the applicability and sensitivity of a biosensor based on SOS...

  13. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  14. Molecular kinetics. Ras activation by SOS: allosteric regulation by altered fluctuation dynamics.

    Science.gov (United States)

    Iversen, Lars; Tu, Hsiung-Lin; Lin, Wan-Chen; Christensen, Sune M; Abel, Steven M; Iwig, Jeff; Wu, Hung-Jen; Gureasko, Jodi; Rhodes, Christopher; Petit, Rebecca S; Hansen, Scott D; Thill, Peter; Yu, Cheng-Han; Stamou, Dimitrios; Chakraborty, Arup K; Kuriyan, John; Groves, Jay T

    2014-07-04

    Activation of the small guanosine triphosphatase H-Ras by the exchange factor Son of Sevenless (SOS) is an important hub for signal transduction. Multiple layers of regulation, through protein and membrane interactions, govern activity of SOS. We characterized the specific activity of individual SOS molecules catalyzing nucleotide exchange in H-Ras. Single-molecule kinetic traces revealed that SOS samples a broad distribution of turnover rates through stochastic fluctuations between distinct, long-lived (more than 100 seconds), functional states. The expected allosteric activation of SOS by Ras-guanosine triphosphate (GTP) was conspicuously absent in the mean rate. However, fluctuations into highly active states were modulated by Ras-GTP. This reveals a mechanism in which functional output may be determined by the dynamical spectrum of rates sampled by a small number of enzymes, rather than the ensemble average. Copyright © 2014, American Association for the Advancement of Science.

  15. Zinc blocks SOS-induced antibiotic resistance via inhibition of RecA in Escherichia coli.

    Science.gov (United States)

    Bunnell, Bryan E; Escobar, Jillian F; Bair, Kirsten L; Sutton, Mark D; Crane, John K

    2017-01-01

    Zinc inhibits the virulence of diarrheagenic E. coli by inducing the envelope stress response and inhibiting the SOS response. The SOS response is triggered by damage to bacterial DNA. In Shiga-toxigenic E. coli, the SOS response strongly induces the production of Shiga toxins (Stx) and of the bacteriophages that encode the Stx genes. In E. coli, induction of the SOS response is accompanied by a higher mutation rate, called the mutator response, caused by a shift to error-prone DNA polymerases when DNA damage is too severe to be repaired by canonical DNA polymerases. Since zinc inhibited the other aspects of the SOS response, we hypothesized that zinc would also inhibit the mutator response, also known as hypermutation. We explored various different experimental paradigms to induce hypermutation triggered by the SOS response, and found that hypermutation was induced not just by classical inducers such as mitomycin C and the quinolone antibiotics, but also by antiviral drugs such as zidovudine and anti-cancer drugs such as 5-fluorouracil, 6-mercaptopurine, and azacytidine. Zinc salts inhibited the SOS response and the hypermutator phenomenon in E. coli as well as in Klebsiella pneumoniae, and was more effective in inhibiting the SOS response than other metals. We then attempted to determine the mechanism by which zinc, applied externally in the medium, inhibits hypermutation. Our results show that zinc interferes with the actions of RecA, and protects LexA from RecA-mediated cleavage, an early step in initiation of the SOS response. The SOS response may play a role in the development of antibiotic resistance and the effect of zinc suggests ways to prevent it.

  16. Zinc blocks SOS-induced antibiotic resistance via inhibition of RecA in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Bryan E Bunnell

    Full Text Available Zinc inhibits the virulence of diarrheagenic E. coli by inducing the envelope stress response and inhibiting the SOS response. The SOS response is triggered by damage to bacterial DNA. In Shiga-toxigenic E. coli, the SOS response strongly induces the production of Shiga toxins (Stx and of the bacteriophages that encode the Stx genes. In E. coli, induction of the SOS response is accompanied by a higher mutation rate, called the mutator response, caused by a shift to error-prone DNA polymerases when DNA damage is too severe to be repaired by canonical DNA polymerases. Since zinc inhibited the other aspects of the SOS response, we hypothesized that zinc would also inhibit the mutator response, also known as hypermutation. We explored various different experimental paradigms to induce hypermutation triggered by the SOS response, and found that hypermutation was induced not just by classical inducers such as mitomycin C and the quinolone antibiotics, but also by antiviral drugs such as zidovudine and anti-cancer drugs such as 5-fluorouracil, 6-mercaptopurine, and azacytidine. Zinc salts inhibited the SOS response and the hypermutator phenomenon in E. coli as well as in Klebsiella pneumoniae, and was more effective in inhibiting the SOS response than other metals. We then attempted to determine the mechanism by which zinc, applied externally in the medium, inhibits hypermutation. Our results show that zinc interferes with the actions of RecA, and protects LexA from RecA-mediated cleavage, an early step in initiation of the SOS response. The SOS response may play a role in the development of antibiotic resistance and the effect of zinc suggests ways to prevent it.

  17. Robust Learning of High-dimensional Biological Networks with Bayesian Networks

    Science.gov (United States)

    Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

    Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.

  18. Congruence for SOS with data

    NARCIS (Netherlands)

    Mousavi, M.R.; Reniers, M.A.; Groote, J.F.

    2004-01-01

    Abstract While studying the specification of the operational semantics of different programming languages and formalisms, one can observe the following three facts. Firstly, Plotkin¿s style of Structured Operational Semantics (SOS) has become a standard in defining operational semantics. Secondly,

  19. [SOS response of DNA repair and genetic cell instability under hypoxic conditions].

    Science.gov (United States)

    Vasil'eva, S V; Strel'tsova, D A

    2011-01-01

    The SOS DNA repair pathway is induced in E. coli as a multifunctional cell response to a wide variety of signals: UV, X or gamma-irradiation, mitomycin C or nalidixic acid treatment, thymine starvation, etc. Triggering of the system can be used as a general and early sign of DNA damage. Additionally, the SOS-response is known to be an "error-prone" DNA repair pathway and one of the sources of genetic instability. Hypoxic conditions are established to be the major factor of genetic instability as well. In this paper we for the first time studied the SOS DNA repair response under hypoxic conditions induced by the well known aerobic SOS-inducers. The SOS DNA repair response was examined as a reaction of E. coli PQ37 [sfiA::lacZ] cells to UVC, NO-donating agents and 4NQO. Here we provide evidence that those agents were able to induce the SOS DNA repair response in E. coli at anaerobic growth conditions. The process does not depend on the transcriptional activity of the universal protein of E. col anaerobic growth Fnr [4Fe-4S]2+ or can not be referred to as an indicator of genetic instability in hypoxic conditions.

  20. Specificity in suppression of SOS expression by recA4162 and uvrD303.

    Science.gov (United States)

    Massoni, Shawn C; Sandler, Steven J

    2013-12-01

    Detection and repair of DNA damage is essential in all organisms and depends on the ability of proteins recognizing and processing specific DNA substrates. In E. coli, the RecA protein forms a filament on single-stranded DNA (ssDNA) produced by DNA damage and induces the SOS response. Previous work has shown that one type of recA mutation (e.g., recA4162 (I298V)) and one type of uvrD mutation (e.g., uvrD303 (D403A, D404A)) can differentially decrease SOS expression depending on the type of inducing treatments (UV damage versus RecA mutants that constitutively express SOS). Here it is tested using other SOS inducing conditions if there is a general feature of ssDNA generated during these treatments that allows recA4162 and uvrD303 to decrease SOS expression. The SOS inducing conditions tested include growing cells containing temperature-sensitive DNA replication mutations (dnaE486, dnaG2903, dnaN159, dnaZ2016 (at 37°C)), a del(polA)501 mutation and induction of Double-Strand Breaks (DSBs). uvrD303 could decrease SOS expression under all conditions, while recA4162 could decrease SOS expression under all conditions except in the polA strain or when DSBs occur. It is hypothesized that recA4162 suppresses SOS expression best when the ssDNA occurs at a gap and that uvrD303 is able to decrease SOS expression when the ssDNA is either at a gap or when it is generated at a DSB (but does so better at a gap). Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Neural networks and statistical learning

    CERN Document Server

    Du, Ke-Lin

    2014-01-01

    Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...

  2. Consequences of SOS1 deficiency: Intracellular physiology and transcription

    KAUST Repository

    Ha, OhDong

    2010-06-01

    As much as there is known about the function of the sodium/proton antiporter SOS1 in plants, recent studies point towards a more general role for this protein. The crucial involvement in salt stress protection is clearly one of its functions –confined to the N-terminus, but the modular structure of the protein includes a segment with several domains that are functionally not studied but comprise more than half of the protein’s length. Additional functions of the protein appear to be an influence on vesicle trafficking, vacuolar pH and general ion homeostasis during salt stress. Eliminating SOS1 leads to the expression of genes that are not strictly salinity stress related. Functions that are regulated in sos1 mutants included pathogen responses, and effects on circadian rhythm.

  3. Collection for SOS animaux

    CERN Multimedia

    2005-01-01

    The Pays de Gex animal shelter is collecting funds. There will be things to buy. You will be able to make a donation and/or become a member of the association or simply get information. SOS Animaux stall (Hall, Build. 60, next to restaurant 1) On Wednesday 23 November 2005 (from 9h - 17h non-stop)

  4. Blending Formal and Informal Learning Networks for Online Learning

    Science.gov (United States)

    Czerkawski, Betül C.

    2016-01-01

    With the emergence of social software and the advance of web-based technologies, online learning networks provide invaluable opportunities for learning, whether formal or informal. Unlike top-down, instructor-centered, and carefully planned formal learning settings, informal learning networks offer more bottom-up, student-centered participatory…

  5. Networked professional learning

    NARCIS (Netherlands)

    Sloep, Peter

    2013-01-01

    Sloep, P. B. (2013). Networked professional learning. In A. Littlejohn, & A. Margaryan (Eds.), Technology-enhanced Professional Learning: Processes, Practices and Tools (pp. 97–108). London: Routledge.

  6. The SOS Suicide Prevention Program: Further Evidence of Efficacy and Effectiveness.

    Science.gov (United States)

    Schilling, Elizabeth A; Aseltine, Robert H; James, Amy

    2016-02-01

    This study replicated and extended previous evaluations of the Signs of Suicide (SOS) prevention program in a high school population using a more rigorous pre-test post-test randomized control design than used in previous SOS evaluations in high schools (Aseltine and DeMartino 2004; Aseltine et al. 2007). SOS was presented to an ethnically diverse group of ninth grade students in technical high schools in Connecticut. After controlling for the pre-test reports of suicide behaviors, exposure to the SOS program was associated with significantly fewer self-reported suicide attempts in the 3 months following the program. Ninth grade students in the intervention group were approximately 64% less likely to report a suicide attempt in the past 3 months compared with students in the control group. Similarly, exposure to the SOS program resulted in greater knowledge of depression and suicide and more favorable attitudes toward (1) intervening with friends who may be exhibiting signs of suicidal intent and (2) getting help for themselves if they were depressed or suicidal. In addition, high-risk SOS participants, defined as those with a lifetime history of suicide attempt, were significantly less likely to report planning a suicide in the 3 months following the program compared to lower-risk participants. Differential attrition is the most serious limitation of the study; participants in the intervention group who reported a suicide attempt in the previous 3 months at baseline were more likely to be missing at post-test than their counterparts in the control group.

  7. Differential requirements of two recA mutants for constitutive SOS expression in Escherichia coli K-12.

    Directory of Open Access Journals (Sweden)

    Jarukit Edward Long

    Full Text Available Repairing DNA damage begins with its detection and is often followed by elicitation of a cellular response. In E. coli, RecA polymerizes on ssDNA produced after DNA damage and induces the SOS Response. The RecA-DNA filament is an allosteric effector of LexA auto-proteolysis. LexA is the repressor of the SOS Response. Not all RecA-DNA filaments, however, lead to an SOS Response. Certain recA mutants express the SOS Response (recA(C in the absence of external DNA damage in log phase cells.Genetic analysis of two recA(C mutants was used to determine the mechanism of constitutive SOS (SOS(C expression in a population of log phase cells using fluorescence of single cells carrying an SOS reporter system (sulAp-gfp. SOS(C expression in recA4142 mutants was dependent on its initial level of transcription, recBCD, recFOR, recX, dinI, xthA and the type of medium in which the cells were grown. SOS(C expression in recA730 mutants was affected by none of the mutations or conditions tested above.It is concluded that not all recA(C alleles cause SOS(C expression by the same mechanism. It is hypothesized that RecA4142 is loaded on to a double-strand end of DNA and that the RecA filament is stabilized by the presence of DinI and destabilized by RecX. RecFOR regulate the activity of RecX to destabilize the RecA filament. RecA730 causes SOS(C expression by binding to ssDNA in a mechanism yet to be determined.

  8. Learning conditional Gaussian networks

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard

    This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

  9. CMOS/SOS 4k Rams hardened to 100 Krads (s:)

    International Nuclear Information System (INIS)

    Napoli, L.S.; Heagerty, W.F.; Smeltzer, R.K.; Yeh, J.L.

    1982-01-01

    Two CMOS/SOS 4K memories were fabricated with a recently developed, hardened SOS process. Memory functionality after radiation doses well in excess of 100 Krads(Si) was demonstrated. The critical device processing steps were identified. The radiationinduced failure mode of the memories is understood in terms of the circuit organization and the radiation behavior of the individual transistors in the memories

  10. Sinusoidal obstruction syndrome (SOS): A light and electron microscopy study in human liver.

    Science.gov (United States)

    Vreuls, C P H; Driessen, A; Olde Damink, S W M; Koek, G H; Duimel, H; van den Broek, M A J; Dejong, C H C; Braet, F; Wisse, E

    2016-05-01

    Oxaliplatin is an important chemotherapeutic agent, used in the treatment of hepatic colorectal metastases, and known to induce the sinusoidal obstruction syndrome (SOS). Pathophysiological knowledge concerning SOS is based on a rat model. Therefore, the aim was to perform a comprehensive study of the features of human SOS, using both light microscopy (LM) and electron microscopy (EM). Included were all patients of whom wedge liver biopsies were collected during a partial hepatectomy for colorectal liver metastases, in a 4-year period. The wedge biopsy were perfusion fixated and processed for LM and EM. The SOS lesions were selected by LM and details were studied using EM. Material was available of 30 patients, of whom 28 patients received neo-adjuvant oxaliplatin. Eighteen (64%) of the 28 patients showed SOS lesions, based on microscopy. The lesions consisted of sinusoidal endothelial cell detachment from the space of Disse on EM. In the enlarged space of Disse a variable amount of erythrocytes were located. Sinusoidal endothelial cell detachment was present in human SOS, accompanied by enlargement of the space of Disse and erythrocytes in this area. These findings, originally described in a rat model, were now for the first time confirmed in human livers under clinically relevant settings. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Overexpression of SOS genes in ciprofloxacin resistant Escherichia coli mutants.

    Science.gov (United States)

    Pourahmad Jaktaji, Razieh; Pasand, Shirin

    2016-01-15

    Fluoroquinolones are important antibiotics for the treatment of urinary tract infections caused by Escherichia coli. Mutational studies have shown that ciprofloxacin, a member of fluoroquinolones induces SOS response and mutagenesis in pathogenic bacteria which in turn develop antibiotic resistance. However, inhibition of SOS response can increase recombination activity which in turn leads to genetic variation. The aim of this study was to measure 5 SOS genes expressions in nine E. coli mutants with different MICs for ciprofloxacin following exposure to ciprofloxacin. Gene expression was assessed by quantitative real time PCR. Gene alteration assessment was conducted by PCR amplification and DNA sequencing. Results showed that the expression of recA was increased in 5 mutants. This overexpression is not related to gene alteration, and enhances the expression of polB and umuCD genes encoding nonmutagenic and mutagenic polymerases, respectively. The direct relationship between the level of SOS expression and the level of resistance to ciprofloxacin was also indicated. It was concluded that novel therapeutic strategy that inhibits RecA activity would enhance the efficiency of common antibiotics against pathogenic bacteria. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.

  13. Influence of the gene xthA in the activation of SOS response of Escherichia coli; Influencia del gen xthA en la activacion de la respuesta SOS de Escherichia coli

    Energy Technology Data Exchange (ETDEWEB)

    Dominguez M, V.

    2013-07-01

    The SOS response is one of the strategies that has Escherichia coli to counteract the lesions in the genetic material. The response is integrated for approximately 60 genes that when are activated they provide to the cell a bigger opportunity to survive. For the activation of this system is necessary that DNA regions of simple chain are generated, in such a way that most of the lesions should be processed, to be able to induce this answer. Some genes that intervene in this procedure, as recO, recB and recJ are recognized since when being exposed to the radiation, their activity SOS is smaller than in a wild strain. In previous works has been studied that to inactivate the genes that are involves in the lesions processing to generate DNA of simple chain, the SOS induction level diminishes with regard to a wild strain, but that when eliminating the genes that are involves directly in the repair, the SOS response increases. In this work a strain with defects in the gene xthA was built, which encodes for an endonuclease AP that participates in the repair mechanism by base excision and was evaluated their sensibility as the activity of the SOS response when exposing it to UV light and gamma radiation. The results showed that the lethality of the strain with the defect is very similar to the wild strain; while the activation level of the SOS response is bigger in comparison with the wild strain when being exposed to UV light; suggesting the existence of an enzyme that recognizes the lesions that produces this radiation, however, is not this the main repair channel, since the survival is similar to that of the wild strain. On the contrary, the results obtained with gamma radiation showed that the lethality diminishes in comparison to that of the wild strain, like the SOS activity; due surely to that the gene product intervenes in the repair for base excision, participating in the formation of the previous substrate to the activation of the SOS response. (Author)

  14. New designing of E-Learning systems with using network learning

    OpenAIRE

    Malayeri, Amin Daneshmand; Abdollahi, Jalal

    2010-01-01

    One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new methodology of E-Learning systems entitle "Network Learning" with review of another aspects of E-Learning systems. Also, we present benefits and advantages of using these systems in educating and fast learning programs. Network Learning can be programmable...

  15. Switching of the positive feedback for RAS activation by a concerted function of SOS membrane association domains.

    Science.gov (United States)

    Nakamura, Yuki; Hibino, Kayo; Yanagida, Toshio; Sako, Yasushi

    2016-01-01

    Son of sevenless (SOS) is a guanine nucleotide exchange factor that regulates cell behavior by activating the small GTPase RAS. Recent in vitro studies have suggested that an interaction between SOS and the GTP-bound active form of RAS generates a positive feedback loop that propagates RAS activation. However, it remains unclear how the multiple domains of SOS contribute to the regulation of the feedback loop in living cells. Here, we observed single molecules of SOS in living cells to analyze the kinetics and dynamics of SOS behavior. The results indicate that the histone fold and Grb2-binding domains of SOS concertedly produce an intermediate state of SOS on the cell surface. The fraction of the intermediated state was reduced in positive feedback mutants, suggesting that the feedback loop functions during the intermediate state. Translocation of RAF, recognizing the active form of RAS, to the cell surface was almost abolished in the positive feedback mutants. Thus, the concerted functions of multiple membrane-associating domains of SOS governed the positive feedback loop, which is crucial for cell fate decision regulated by RAS.

  16. Characterization of Salt Overly Sensitive 1 (SOS1) gene homoeologs in quinoa (Chenopodium quinoa Willd.).

    Science.gov (United States)

    Maughan, P J; Turner, T B; Coleman, C E; Elzinga, D B; Jellen, E N; Morales, J A; Udall, J A; Fairbanks, D J; Bonifacio, A

    2009-07-01

    Salt tolerance is an agronomically important trait that affects plant species around the globe. The Salt Overly Sensitive 1 (SOS1) gene encodes a plasma membrane Na+/H+ antiporter that plays an important role in germination and growth of plants in saline environments. Quinoa (Chenopodium quinoa Willd.) is a halophytic, allotetraploid grain crop of the family Amaranthaceae with impressive nutritional content and an increasing worldwide market. Many quinoa varieties have considerable salt tolerance, and research suggests quinoa may utilize novel mechanisms to confer salt tolerance. Here we report the cloning and characterization of two homoeologous SOS1 loci (cqSOS1A and cqSOS1B) from C. quinoa, including full-length cDNA sequences, genomic sequences, relative expression levels, fluorescent in situ hybridization (FISH) analysis, and a phylogenetic analysis of SOS1 genes from 13 plant taxa. The cqSOS1A and cqSOS1B genes each span 23 exons spread over 3477 bp and 3486 bp of coding sequence, respectively. These sequences share a high level of similarity with SOS1 homologs of other species and contain two conserved domains, a Nhap cation-antiporter domain and a cyclic-nucleotide binding domain. Genomic sequence analysis of two BAC clones (98 357 bp and 132 770 bp) containing the homoeologous SOS1 genes suggests possible conservation of synteny across the C. quinoa sub-genomes. This report represents the first molecular characterization of salt-tolerance genes in a halophytic species in the Amaranthaceae as well as the first comparative analysis of coding and non-coding DNA sequences of the two homoeologous genomes of C. quinoa.

  17. SoS Notebook: An Interactive Multi-Language Data Analysis Environment.

    Science.gov (United States)

    Peng, Bo; Wang, Gao; Ma, Jun; Leong, Man Chong; Wakefield, Chris; Melott, James; Chiu, Yulun; Du, Di; Weinstein, John N

    2018-05-22

    Complex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share, and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking. We developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications. SoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license. bpeng@mdanderson.org.

  18. Effect of radiation doses rate on SOS response induction in irradiated Escherichia coli Cells

    International Nuclear Information System (INIS)

    Cuetara Lugo, Elizabeth B.; Fuentes Lorenzo, Jorge L.; Almeida Varela, Eliseo; Prieto Miranda, Enrique F.; Sanchez Lamar, Angel; Llagostera Casal, Montserrat

    2005-01-01

    The present work is aimed to study the effect of radiation dose rate on the induction of SOS response in Escherichia coli cells. We measured the induction of sul A reporter gene in PQ-37 (SOS Chromotest) cells. Lead devises were built with different diameter and these were used for diminishing the dose rate of PX- -30M irradiator. Our results show that radiation doses rate significantly modifies the induction of SOS response. Induction factor increases proportionally to doses rate in Escherichia coli cells defective to nucleotide excision repair (uvrA), but not in wild type cells. We conclude that the dose rate affects the level of induction of SOS response

  19. SOS response activation and competence development are antagonistic mechanisms in Streptococcus thermophilus.

    Science.gov (United States)

    Boutry, Céline; Delplace, Brigitte; Clippe, André; Fontaine, Laetitia; Hols, Pascal

    2013-02-01

    Streptococcus includes species that either contain or lack the LexA-like repressor (HdiR) of the classical SOS response. In Streptococcus pneumoniae, a species which belongs to the latter group, SOS response inducers (e.g., mitomycin C [Mc] and fluoroquinolones) were shown to induce natural transformation, leading to the hypothesis that DNA damage-induced competence could contribute to genomic plasticity and stress resistance. Using reporter strains and microarray experiments, we investigated the impact of the SOS response inducers mitomycin C and norfloxacin and the role of HdiR on competence development in Streptococcus thermophilus. We show that both the addition of SOS response inducers and HdiR inactivation have a dual effect, i.e., induction of the expression of SOS genes and reduction of transformability. Reduction of transformability results from two different mechanisms, since HdiR inactivation has no major effect on the expression of competence (com) genes, while mitomycin C downregulates the expression of early and late com genes in a dose-dependent manner. The downregulation of com genes by mitomycin C was shown to take place at the level of the activation of the ComRS signaling system by an unknown mechanism. Conversely, we show that a ComX-deficient strain is more resistant to mitomycin C and norfloxacin in a viability plate assay, which indicates that competence development negatively affects the resistance of S. thermophilus to DNA-damaging agents. Altogether, our results strongly suggest that SOS response activation and competence development are antagonistic processes in S. thermophilus.

  20. Escherichia coli DinB inhibits replication fork progression without significantly inducing the SOS response.

    Science.gov (United States)

    Mori, Tetsuya; Nakamura, Tatsuro; Okazaki, Naoto; Furukohri, Asako; Maki, Hisaji; Akiyama, Masahiro Tatsumi

    2012-01-01

    The SOS response is readily triggered by replication fork stalling caused by DNA damage or a dysfunctional replicative apparatus in Escherichia coli cells. E. coli dinB encodes DinB DNA polymerase and its expression is upregulated during the SOS response. DinB catalyzes translesion DNA synthesis in place of a replicative DNA polymerase III that is stalled at a DNA lesion. We showed previously that DNA replication was suppressed without exogenous DNA damage in cells overproducing DinB. In this report, we confirm that this was due to a dose-dependent inhibition of ongoing replication forks by DinB. Interestingly, the DinB-overproducing cells did not significantly induce the SOS response even though DNA replication was perturbed. RecA protein is activated by forming a nucleoprotein filament with single-stranded DNA, which leads to the onset of the SOS response. In the DinB-overproducing cells, RecA was not activated to induce the SOS response. However, the SOS response was observed after heat-inducible activation in strain recA441 (encoding a temperature-sensitive RecA) and after replication blockage in strain dnaE486 (encoding a temperature-sensitive catalytic subunit of the replicative DNA polymerase III) at a non-permissive temperature when DinB was overproduced in these cells. Furthermore, since catalytically inactive DinB could avoid the SOS response to a DinB-promoted fork block, it is unlikely that overproduced DinB takes control of primer extension and thus limits single-stranded DNA. These observations suggest that DinB possesses a feature that suppresses DNA replication but does not abolish the cell's capacity to induce the SOS response. We conclude that DinB impedes replication fork progression in a way that does not activate RecA, in contrast to obstructive DNA lesions and dysfunctional replication machinery.

  1. A syntactic commutativity format for SOS

    NARCIS (Netherlands)

    Mousavi, M.R.; Reniers, M.A.; Groote, J.F.

    2005-01-01

    Considering operators defined using Structural Operational Semantics (SOS), commutativity axioms are intuitive properties that hold for many of them. Proving this intuition is usually a laborious task, requiring several pages of boring and standard proof. To save this effort, we propose a syntactic

  2. Gain-of-function SOS1 mutations cause a distinctive form of noonansyndrome

    Energy Technology Data Exchange (ETDEWEB)

    Tartaglia, Marco; Pennacchio, Len A.; Zhao, Chen; Yadav, KamleshK.; Fodale, Valentina; Sarkozy, Anna; Pandit, Bhaswati; Oishi, Kimihiko; Martinelli, Simone; Schackwitz, Wendy; Ustaszewska, Anna; Martin, Joes; Bristow, James; Carta, Claudio; Lepri, Francesca; Neri, Cinzia; Vasta,Isabella; Gibson, Kate; Curry, Cynthia J.; Lopez Siguero, Juan Pedro; Digilio, Maria Cristina; Zampino, Giuseppe; Dallapiccola, Bruno; Bar-Sagi, Dafna; Gelb, Brude D.

    2006-09-01

    Noonan syndrome (NS) is a developmental disordercharacterized by short stature, facial dysmorphia, congenital heartdefects and skeletal anomalies1. Increased RAS-mitogenactivated proteinkinase (MAPK) signaling due to PTPN11 and KRAS mutations cause 50 percentof NS2-6. Here, we report that 22 of 129 NS patients without PTPN11 orKRAS mutation (17 percent) have missense mutations in SOS1, which encodesa RAS-specific guanine nucleotide exchange factor (GEF). SOS1 mutationscluster at residues implicated in the maintenance of SOS1 in itsautoinhibited form and ectopic expression of two NS-associated mutantsinduced enhanced RAS activation. The phenotype associated with SOS1defects is distinctive, although within NS spectrum, with a highprevalence of ectodermal abnormalities but generally normal developmentand linear growth. Our findings implicate for the first timegain-of-function mutations in a RAS GEF in inherited disease and define anew mechanism by which upregulation of the RAS pathway can profoundlychange human development.

  3. SOS hotline for women victims of discrimination at the workplace

    OpenAIRE

    Dobrosavljević-Grujić Ljiljana S.

    2004-01-01

    SOS hotline for women victims of discrimination at the workplace offers free legal assistance to women, whenever their labor rights are endangered. If the dispute cannot be resolved peacefully by mediation between employer and employees, female lawyer skilled for the labor law starts up judicial proceedings. Some characteristic cases of discrimination of women from the practice of SOS telephone, such as dismissal from the work, physical violence and sexual blackmail, are presented in the paper.

  4. Activation of the plasma membrane Na/H antiporter salt-overly-sensitive 1 (SOS1) by phosphorylation of an auto-inhibitory C-terminal domain

    KAUST Repository

    Quintero, Francisco J.; Martí nez-Atienza, Juliana; Villalta, Irene; Jiang, Xingyu; Kim, Woeyeon; Ali, Zhair; Fujii, Hiroaki; Mendoza, Imelda; Yun, Daejin; Zhu, Jian-Kang; Pardo, José Manuel

    2011-01-01

    The plasma membrane sodium/proton exchanger Salt-Overly-Sensitive 1 (SOS1) is a critical salt tolerance determinant in plants. The SOS2-SOS3 calcium-dependent protein kinase complex upregulates SOS1 activity, but the mechanistic details of this crucial event remain unresolved. Here we show that SOS1 is maintained in a resting state by a C-terminal auto-inhibitory domain that is the target of SOS2-SOS3. The auto-inhibitory domain interacts intramolecularly with an adjacent domain of SOS1 that is essential for activity. SOS1 is relieved from auto-inhibition upon phosphorylation of the auto-inhibitory domain by SOS2-SOS3. Mutation of the SOS2 phosphorylation and recognition site impeded the activation of SOS1 in vivo and in vitro. Additional amino acid residues critically important for SOS1 activity and regulation were identified in a genetic screen for hypermorphic alleles.

  5. Activation of the plasma membrane Na/H antiporter salt-overly-sensitive 1 (SOS1) by phosphorylation of an auto-inhibitory C-terminal domain

    KAUST Repository

    Quintero, Francisco J.

    2011-01-24

    The plasma membrane sodium/proton exchanger Salt-Overly-Sensitive 1 (SOS1) is a critical salt tolerance determinant in plants. The SOS2-SOS3 calcium-dependent protein kinase complex upregulates SOS1 activity, but the mechanistic details of this crucial event remain unresolved. Here we show that SOS1 is maintained in a resting state by a C-terminal auto-inhibitory domain that is the target of SOS2-SOS3. The auto-inhibitory domain interacts intramolecularly with an adjacent domain of SOS1 that is essential for activity. SOS1 is relieved from auto-inhibition upon phosphorylation of the auto-inhibitory domain by SOS2-SOS3. Mutation of the SOS2 phosphorylation and recognition site impeded the activation of SOS1 in vivo and in vitro. Additional amino acid residues critically important for SOS1 activity and regulation were identified in a genetic screen for hypermorphic alleles.

  6. Design rules for RCA self-aligned silicon-gate CMOS/SOS process

    Science.gov (United States)

    1977-01-01

    The CMOS/SOS design rules prepared by the RCA Solid State Technology Center (SSTC) are described. These rules specify the spacing and width requirements for each of the six design levels, the seventh level being used to define openings in the passivation level. An associated report, entitled Silicon-Gate CMOS/SOS Processing, provides further insight into the usage of these rules.

  7. Rare variants in SOS2 and LZTR1 are associated with Noonan syndrome.

    Science.gov (United States)

    Yamamoto, Guilherme Lopes; Aguena, Meire; Gos, Monika; Hung, Christina; Pilch, Jacek; Fahiminiya, Somayyeh; Abramowicz, Anna; Cristian, Ingrid; Buscarilli, Michelle; Naslavsky, Michel Satya; Malaquias, Alexsandra C; Zatz, Mayana; Bodamer, Olaf; Majewski, Jacek; Jorge, Alexander A L; Pereira, Alexandre C; Kim, Chong Ae; Passos-Bueno, Maria Rita; Bertola, Débora Romeo

    2015-06-01

    Noonan syndrome is an autosomal dominant, multisystemic disorder caused by dysregulation of the RAS/mitogen activated protein kinase (MAPK) pathway. Heterozygous, pathogenic variants in 11 known genes account for approximately 80% of cases. The identification of novel genes associated with Noonan syndrome has become increasingly challenging, since they might be responsible for very small fractions of the cases. A cohort of 50 Brazilian probands negative for pathogenic variants in the known genes associated with Noonan syndrome was tested through whole-exome sequencing along with the relatives in the familial cases. Families from the USA and Poland with mutations in the newly identified genes were included subsequently. We identified rare, segregating or de novo missense variants in SOS2 and LZTR1 in 4% and 8%, respectively, of the 50 Brazilian probands. SOS2 and LZTR1 variants were also found to segregate in one American and one Polish family. Notably, SOS2 variants were identified in patients with marked ectodermal involvement, similar to patients with SOS1 mutations. We identified two novel genes, SOS2 and LZTR1, associated with Noonan syndrome, thereby expanding the molecular spectrum of RASopathies. Mutations in these genes are responsible for approximately 3% of all patients with Noonan syndrome. While SOS2 is a natural candidate, because of its homology with SOS1, the functional role of LZTR1 in the RAS/MAPK pathway is not known, and it could not have been identified without the large pedigrees. Additional functional studies are needed to elucidate the role of LZTR1 in RAS/MAPK signalling and in the pathogenesis of Noonan syndrome. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  8. SOS reaction kinetics of bacterial cells induced by ultraviolet radiation and α particles

    International Nuclear Information System (INIS)

    Bonev, M.; Kolev, S.

    2000-01-01

    It is the purpose of the work to apply the SOS lux test for detecting α particles, as well as to study the SOS system kinetics. Two strains with plasmid pPLS-1 are used: wild type C600 lux and its isogen lysogen with α prophage one. Irradiation is done on dacron nuclear filters. The source of α particles is Am 241 with power 5 Gy/min, and the ultraviolet source - a lamp emitting rays with wave length 254 nm. The light yield is measured by installations made up of scintilometer VA-S-968, High-voltage electric power, and one channel analyzer Strahlugsmessgerat 20046. The SOS lux text is based on the recombinant plasmid pPLS-1 which is a derivative of pBR322 where the lux gene is set under the control of an SOS promoter. E coly recA + strains containing the construction produce considerable amount of photons in the visible zone following treatment with agents damaging the DNA of cells. The kinetic curves of SOS response are obtained after irradiation with α particles and UV rays. DNA damaging agents cause an increase in the initial SOS response rate in the range od smaller doses, and a decrease reaching to block of the one in the high doses range. The light yield of lysogenic cells is lower. As compared to nonelysogene ones. DNA damage caused by α particles are more difficult to repair as compared to pyrimidine dimers. (author)

  9. A hierarchy of SOS rule formats

    NARCIS (Netherlands)

    Groote, J.F.; Mousavi, M.R.; Reniers, M.A.; Mosses, P.D.; Ulidowski, I.

    2006-01-01

    In 1981 Structural Operational Semantics (SOS) was introduced as a systematic way to define operational semantics of programming languages by a set of rules of a certain shape [G.D. Plotkin. A structural approach to operational semantics. Technical Report DAIMI FN-19, Computer Science Department,

  10. Fastest learning in small-world neural networks

    International Nuclear Information System (INIS)

    Simard, D.; Nadeau, L.; Kroeger, H.

    2005-01-01

    We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition

  11. Hydrothermal Carbonization of Spent Osmotic Solution (SOS Generated from Osmotic Dehydration of Blueberries

    Directory of Open Access Journals (Sweden)

    Kaushlendra Singh

    2014-09-01

    Full Text Available Hydrothermal carbonization of spent osmotic solution (SOS, a waste generated from osmotic dehydration of fruits, has the potential of transformation into hydrochars, a value-added product, while reducing cost and overall greenhouse gas emissions associated with waste disposal. Osmotic solution (OS and spent osmotic solution (SOS generated from the osmotic dehydration of blueberries were compared for their thermo-chemical decomposition behavior and hydrothermal carbonization. OS and SOS samples were characterized for total solids, elemental composition, and thermo-gravimetric analysis (TGA. In addition, hydrothermal carbonization was performed at 250 °C and for 30 min to produce hydrochars. The hydrochars were characterized for elemental composition, Brunauer-Emmett-Teller (BET surface area, particle shape and surface morphology. TGA results show that the SOS sample loses more weight in the lower temperature range than the OS sample. Both samples produced, approximately, 40%–42% (wet-feed basis hydrochar during hydrothermal carbonization but with different properties. The OS sample produced hydrochar, which had spherical particles of 1.79 ± 1.30 μm diameter with a very smooth surface. In contrast, the SOS sample produced hydrochar with no definite particle shape but with a raspberry-like surface.

  12. The Integration of Personal Learning Environments & Open Network Learning Environments

    Science.gov (United States)

    Tu, Chih-Hsiung; Sujo-Montes, Laura; Yen, Cherng-Jyh; Chan, Junn-Yih; Blocher, Michael

    2012-01-01

    Learning management systems traditionally provide structures to guide online learners to achieve their learning goals. Web 2.0 technology empowers learners to create, share, and organize their personal learning environments in open network environments; and allows learners to engage in social networking and collaborating activities. Advanced…

  13. SOS hotline for women victims of discrimination at the workplace

    Directory of Open Access Journals (Sweden)

    Dobrosavljević-Grujić Ljiljana S.

    2004-01-01

    Full Text Available SOS hotline for women victims of discrimination at the workplace offers free legal assistance to women, whenever their labor rights are endangered. If the dispute cannot be resolved peacefully by mediation between employer and employees, female lawyer skilled for the labor law starts up judicial proceedings. Some characteristic cases of discrimination of women from the practice of SOS telephone, such as dismissal from the work, physical violence and sexual blackmail, are presented in the paper.

  14. Expansion of the SOS regulon of Vibrio cholerae through extensive transcriptome analysis and experimental validation.

    Science.gov (United States)

    Krin, Evelyne; Pierlé, Sebastian Aguilar; Sismeiro, Odile; Jagla, Bernd; Dillies, Marie-Agnès; Varet, Hugo; Irazoki, Oihane; Campoy, Susana; Rouy, Zoé; Cruveiller, Stéphane; Médigue, Claudine; Coppée, Jean-Yves; Mazel, Didier

    2018-05-21

    The SOS response is an almost ubiquitous response of cells to genotoxic stresses. The full complement of genes in the SOS regulon for Vibrio species has only been addressed through bioinformatic analyses predicting LexA binding box consensus and in vitro validation. Here, we perform whole transcriptome sequencing from Vibrio cholerae treated with mitomycin C as an SOS inducer to characterize the SOS regulon and other pathways affected by this treatment. Comprehensive transcriptional profiling allowed us to define the full landscape of promoters and transcripts active in V. cholerae. We performed extensive transcription start site (TSS) mapping as well as detection/quantification of the coding and non-coding RNA (ncRNA) repertoire in strain N16961. To improve TSS detection, we developed a new technique to treat RNA extracted from cells grown in various conditions. This allowed for identification of 3078 TSSs with an average 5'UTR of 116 nucleotides, and peak distribution between 16 and 64 nucleotides; as well as 629 ncRNAs. Mitomycin C treatment induced transcription of 737 genes and 28 ncRNAs at least 2 fold, while it repressed 231 genes and 17 ncRNAs. Data analysis revealed that in addition to the core genes known to integrate the SOS regulon, several metabolic pathways were induced. This study allowed for expansion of the Vibrio SOS regulon, as twelve genes (ubiEJB, tatABC, smpA, cep, VC0091, VC1190, VC1369-1370) were found to be co-induced with their adjacent canonical SOS regulon gene(s), through transcriptional read-through. Characterization of UV and mitomycin C susceptibility for mutants of these newly identified SOS regulon genes and other highly induced genes and ncRNAs confirmed their role in DNA damage rescue and protection. We show that genotoxic stress induces a pervasive transcriptional response, affecting almost 20% of the V. cholerae genes. We also demonstrate that the SOS regulon is larger than previously known, and its syntenic organization is

  15. Inhibitors of LexA Autoproteolysis and the Bacterial SOS Response Discovered by an Academic-Industry Partnership.

    Science.gov (United States)

    Mo, Charlie Y; Culyba, Matthew J; Selwood, Trevor; Kubiak, Jeffrey M; Hostetler, Zachary M; Jurewicz, Anthony J; Keller, Paul M; Pope, Andrew J; Quinn, Amy; Schneck, Jessica; Widdowson, Katherine L; Kohli, Rahul M

    2018-03-09

    The RecA/LexA axis of the bacterial DNA damage (SOS) response is a promising, yet nontraditional, drug target. The SOS response is initiated upon genotoxic stress, when RecA, a DNA damage sensor, induces LexA, the SOS repressor, to undergo autoproteolysis, thereby derepressing downstream genes that can mediate DNA repair and accelerate mutagenesis. As genetic inhibition of the SOS response sensitizes bacteria to DNA damaging antibiotics and decreases acquired resistance, inhibitors of the RecA/LexA axis could potentiate our current antibiotic arsenal. Compounds targeting RecA, which has many mammalian homologues, have been reported; however, small-molecules targeting LexA autoproteolysis, a reaction unique to the prokaryotic SOS response, have remained elusive. Here, we describe the logistics and accomplishments of an academic-industry partnership formed to pursue inhibitors against the RecA/LexA axis. A novel fluorescence polarization assay reporting on RecA-induced self-cleavage of LexA enabled the screening of 1.8 million compounds. Follow-up studies on select leads show distinct activity patterns in orthogonal assays, including several with activity in cell-based assays reporting on SOS activation. Mechanistic assays demonstrate that we have identified first-in-class small molecules that specifically target the LexA autoproteolysis step in SOS activation. Our efforts establish a realistic example for navigating academic-industry partnerships in pursuit of anti-infective drugs and offer starting points for dedicated lead optimization of SOS inhibitors that could act as adjuvants for current antibiotics.

  16. Stent-over-sponge (SOS): a novel technique complementing endosponge therapy for foregut leaks and perforations.

    Science.gov (United States)

    Valli, Piero V; Mertens, Joachim C; Kröger, Arne; Gubler, Christoph; Gutschow, Christian; Schneider, Paul M; Bauerfeind, Peter

    2018-02-01

     Endoluminal vacuum therapy (EVT) has evolved as a promising option for endoscopic treatment of foregut wall injuries in addition to the classic closure techniques using clips or stents. To improve vacuum force and maintain esophageal passage, we combined endosponge treatment with a partially covered self-expandable metal stent (stent-over-sponge; SOS).  Twelve patients with infected upper gastrointestinal wall defects were treated with the SOS technique.  Indications for SOS were anastomotic leakage after surgery (n = 11) and chronic foregut fistula (n = 1). SOS treatment was used as a first-line treatment in seven patients with a success rate of 71.4 % (5/7) and as a second-line treatment after failed previous EVT treatment in five patients (success rate 80 %; 4/5). Overall, SOS treatment was successful in 75 % of patients (9/12). No severe adverse events occurred. CONCLUSION : SOS is an effective method to treat severely infected foregut wall defects in patients where EVT has failed, and also as a first-line treatment. Comparative prospective studies are needed to confirm our preliminary results. © Georg Thieme Verlag KG Stuttgart · New York.

  17. Learning Networks for Professional Development & Lifelong Learning

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    Sloep, P. B. (2009). Learning Networks for Professional Development & Lifelong Learning. Presentation at a NeLLL seminar with Etienne Wenger held at the Open Universiteit Nederland. September, 10, 2009, Heerlen, The Netherlands.

  18. [Expressions of Ras and Sos1 in epithelial ovarian cancer tissues and their clinical significance].

    Science.gov (United States)

    Xiao, Zheng-Hua; Linghu, Hua; Liu, Qian-Fen

    2016-11-20

    To detect the expressions of Ras and Sos1 proteins in human epithelial ovarian cancer (EOC) tissues and explore their correlation with the clinicopathological features of the patients. The expressions of Ras and Sos1 proteins were detected immunohistochemically in 62 EOC tissues, 5 borderline ovarian cancer tissues, 15 benign epithelial ovarian neoplasm tissues, and 18 normal ovarian tissues. The EOC tissues showed significantly higher expression levels of both Ras and Sos1 than the other tissues tested (Ptissues, Ras and Sos1 proteins were expressed mostly on the cell membrane and in the cytoplasm. The expression level of Ras was correlated with pathological types of the tumor (Ptissue-specific variation of Ras expression can lend support to a specific diagnosis of ovarian serous adenocarcinoma. The association of Ras and Sos1 protein expression with the tumor-free survival time of the patients awaits further investigation with a larger sample size.

  19. Genetic analysis of the SOS response of Escherichia coli

    International Nuclear Information System (INIS)

    Mount, D.W.; Wertman, K.F.; Ennis, D.G.; Peterson, K.R.; Fisher, B.L.; Lyons, G.

    1983-01-01

    In the SOS response, a large number of E. coli genes having different functions are derepressed when the cellular DNA is damaged. This derepression occurs through inactivation of a repressor, the product of the lexA gene, by a protease activity of the recA gene product. The protease is thought to be activated in response to changes in DNA metabolism which follow the damage. After the SOS functions have acted, the protease activity declines and repression is again established. Because the DNA sequence of both lexA and recA have been determined, it is possible to induce many mutations in their regulatory and structural regions in order to analyze further the control of the SOS response. We are studying the effects of mutations in both the lexA and recA regulatory regions, and mutations which affect the protease activity or the sensitivity of repressor to the protease. Finally, we are using genetic methods to analyze a newly identified requirement for recA protein, induced mutagenesis in cells lacking repressor. 16 references, 3 figures

  20. Edmodo social learning network for elementary school mathematics learning

    Science.gov (United States)

    Ariani, Y.; Helsa, Y.; Ahmad, S.; Prahmana, RCI

    2017-12-01

    A developed instructional media can be as printed media, visual media, audio media, and multimedia. The development of instructional media can also take advantage of technological development by utilizing Edmodo social network. This research aims to develop a digital classroom learning model using Edmodo social learning network for elementary school mathematics learning which is practical, valid and effective in order to improve the quality of learning activities. The result of this research showed that the prototype of mathematics learning device for elementary school students using Edmodo was in good category. There were 72% of students passed the assessment as a result of Edmodo learning. Edmodo has become a promising way to engage students in a collaborative learning process.

  1. Phenomenology of an inducible mutagenic DNA repair pathway in Escherichia coli: SOS repair hypothesis

    International Nuclear Information System (INIS)

    Radman, M.

    1974-01-01

    A hypothesis is proposed according to which E. coli possesses an inducible DNA repair system. This hypothetical repair, which we call SOS repair, is manifested only following damage to DNA, and requires de novo protein synthesis. SOS repair in E. coli requires some known genetic elements: recA + , lex + and probably zab + . Mutagenesis by ultraviolet light is observed only under conditions of functional SOS repair: we therefore suspect that this is a mutation-prone repair. A number of phenomena and experiments is reviewed which at this point can best be interpreted in terms of an inducible mutagenic DNA repair system. Two recently discovered phenomena support the proposed hypothesis: existence of a mutant (tif) which, after a shift to elevated temperature, mimicks the effect of uv irradiation in regard to repair of phage lambda and uv mutagenesis, apparent activation of SOS repair by introduction into the recipient cell of damaged plasmid or Hfr DNA. Several specific predictions based on SOS repair hypothesis are presented in order to stimulate further experimental tests. (U.S.)

  2. Entropy Learning in Neural Network

    Directory of Open Access Journals (Sweden)

    Geok See Ng

    2017-12-01

    Full Text Available In this paper, entropy term is used in the learning phase of a neural network.  As learning progresses, more hidden nodes get into saturation.  The early creation of such hidden nodes may impair generalisation.  Hence entropy approach is proposed to dampen the early creation of such nodes.  The entropy learning also helps to increase the importance of relevant nodes while dampening the less important nodes.  At the end of learning, the less important nodes can then be eliminated to reduce the memory requirements of the neural network.

  3. Genetic characterization of the inducible SOS-like system of Bacillus subtilis

    Energy Technology Data Exchange (ETDEWEB)

    Love, P.E.; Yasbin, R.E.

    1984-12-01

    The SOS-like system of Bacillus subtilis consists of several coordinately induced phenomena which are expressed after cellular insult such as DNA damage of inhibition of DNA replication. Mutagenesis of the bacterial chromosomes and the development of maintenance of competence also appear to be involved in the SOS-like response in this bacterium. The genetic characterization of the SOS-like system has involved an analysis of (i) the effects of various DNA repair mutations on the expression of inducible phenomena and (ii) the tsi-23 mutation, which renders host strains thermally inducible for each of the SOS-like functions. Bacterial filamentation was unaffected by any of the DNA repair mutations studied. In contrast, the induction of prophage after thermal or UV pretreatment was abolished in strains carrying the recE4, recA1, recB2, or recG13 mutation. The Weigle reactivation of UV-damaged bacteriophage was also inhibited by the recE4, recA1, recB2, or recG13 mutation, whereas levels of Weigle reactivation were lower in strains which carried the uvrA42, polA5, or rec-961 mutation than in the DNA repair-proficient strain. Strains which carried the recE4 mutation were incapable of chromosomal DNA-mediated transformation, and the frequency of this event was decreased in strains carrying recA1, recB2, or tsi-23 mutation. Plasmid DNA transformation efficiency was decreased only in strains carrying the tsi-23 mutation in addition to the recE4, recA1, or recB2 mutation. The results indicate that the SOS-like system of B. subtilis is regulated at different levels by two or more gene products. In this report, the current data regarding the genetic regulation of inducible phenomena are summarized, and a model is proposed to explain the mechanism of SOS-like induction in B. subtillis. 50 references, 3 figures, 6 tables.

  4. Genetic requirements for high constitutive SOS expression in recA730 mutants of Escherichia coli.

    Science.gov (United States)

    Vlašić, Ignacija; Šimatović, Ana; Brčić-Kostić, Krunoslav

    2011-09-01

    The RecA protein in its functional state is in complex with single-stranded DNA, i.e., in the form of a RecA filament. In SOS induction, the RecA filament functions as a coprotease, enabling the autodigestion of the LexA repressor. The RecA filament can be formed by different mechanisms, but all of them require three enzymatic activities essential for the processing of DNA double-stranded ends. These are helicase, 5'-3' exonuclease, and RecA loading onto single-stranded DNA (ssDNA). In some mutants, the SOS response can be expressed constitutively during the process of normal DNA metabolism. The RecA730 mutant protein is able to form the RecA filament without the help of RecBCD and RecFOR mediators since it better competes with the single-strand binding (SSB) protein for ssDNA. As a consequence, the recA730 mutants show high constitutive SOS expression. In the study described in this paper, we studied the genetic requirements for constitutive SOS expression in recA730 mutants. Using a β-galactosidase assay, we showed that the constitutive SOS response in recA730 mutants exhibits different requirements in different backgrounds. In a wild-type background, the constitutive SOS response is partially dependent on RecBCD function. In a recB1080 background (the recB1080 mutation retains only helicase), constitutive SOS expression is partially dependent on RecBCD helicase function and is strongly dependent on RecJ nuclease. Finally, in a recB-null background, the constitutive SOS expression of the recA730 mutant is dependent on the RecJ nuclease. Our results emphasize the importance of the 5'-3' exonuclease for high constitutive SOS expression in recA730 mutants and show that RecBCD function can further enhance the excellent intrinsic abilities of the RecA730 protein in vivo. Copyright © 2011, American Society for Microbiology. All Rights Reserved.

  5. Paraísos fiscales en la globalización financiera

    Directory of Open Access Journals (Sweden)

    Alberto Garzón Espinosa

    2011-10-01

    Full Text Available Los paraísos fiscales son espacios financieros caracterizados ante todo por su baja o nula tributación. En este artículo examinaremos con detalle el uso de los mismos por parte de los agentes económicos, centrándonos especialmente en los bancos y los fondos de inversión colectiva. No obstante, como elementos clave de un nuevo contexto financiero los paraísos fiscales han tenido un papel fundamental en la gestación y expansión de todas las crisis financieras recientes, razón por la cual también estudiaremos las consecuencias que la existencia misma de los paraísos fiscales tiene sobre la economía y el sistema financiero.Palabras clave: Paraísos fiscales, globalización financiera, neoliberalismo_______________Abstract:The tax haven are financial spaces which it characterize for its shorts taxations. In this article we will analyze the use of that by the economic agent, specially the banks and the funds of collective investment. However, like key elements of the new financial context, the tax haven was been a leading role in gestation and expansion of all financial crisis of our days. For that, we will study the consequences of this fact in the economy and financial system.Keywords: tax haven, financial globalization, neoliberalism.

  6. ExplorOcean H2O SOS: Help Heal the Ocean-Student Operated Solutions: Operation Climate Change

    Science.gov (United States)

    Weiss, N.; Wood, J. H.

    2016-12-01

    The ExplorOcean H2O SOS: Help Heal the Ocean—Student Operated Solutions: Operation Climate Change, teaches middle and high school students about ocean threats related to climate change through hands-on activities and learning experiences in the field. During each session (in-class or after-school as a club), students build an understanding about how climate change impacts our oceans using resources provided by ExplorOcean (hands-on activities, presentations, multi-media). Through a student leadership model, students present lessons to each other, interweaving a deep learning of science, 21st century technology, communication skills, and leadership. After participating in learning experiences and activities related to 6 key climate change concepts: 1) Introduction to climate change, 2) Increased sea temperatures, 3) Ocean acidification, 4) Sea level rise, 5) Feedback mechanisms, and 6) Innovative solutions. H2O SOS- Operation Climate change participants select one focus issue and use it to design a multi-pronged campaign to increase awareness about this issue in their local community. The campaign includes social media, an interactive activity, and a visual component. All participating clubs that meet participation and action goals earn a field trip to ExplorOcean where they dive deeper into their selected issue through hands-on activities, real-world investigations, and interviews or presentations with experts. In addition to self-selected opportunities to showcase their focus issue, teams will participate in one of several key events identified by ExplorOcean, including ExplorOcean's annual World Oceans Day Expo.

  7. Leptospira interrogans serovar copenhageni harbors two lexA genes involved in SOS response.

    Directory of Open Access Journals (Sweden)

    Luciane S Fonseca

    Full Text Available Bacteria activate a regulatory network in response to the challenges imposed by DNA damage to genetic material, known as the SOS response. This system is regulated by the RecA recombinase and by the transcriptional repressor lexA. Leptospira interrogans is a pathogen capable of surviving in the environment for weeks, being exposed to a great variety of stress agents and yet retaining its ability to infect the host. This study aims to investigate the behavior of L. interrogans serovar Copenhageni after the stress induced by DNA damage. We show that L. interrogans serovar Copenhageni genome contains two genes encoding putative LexA proteins (lexA1 and lexA2 one of them being potentially acquired by lateral gene transfer. Both genes are induced after DNA damage, but the steady state levels of both LexA proteins drop, probably due to auto-proteolytic activity triggered in this condition. In addition, seven other genes were up-regulated following UV-C irradiation, recA, recN, dinP, and four genes encoding hypothetical proteins. This set of genes is potentially regulated by LexA1, as it showed binding to their promoter regions. All these regions contain degenerated sequences in relation to the previously described SOS box, TTTGN 5CAAA. On the other hand, LexA2 was able to bind to the palindrome TTGTAN10TACAA, found in its own promoter region, but not in the others. Therefore, the L. interrogans serovar Copenhageni SOS regulon may be even more complex, as a result of LexA1 and LexA2 binding to divergent motifs. New possibilities for DNA damage response in Leptospira are expected, with potential influence in other biological responses such as virulence.

  8. Approach for targeting Ras with small molecules that activate SOS-mediated nucleotide exchange.

    Science.gov (United States)

    Burns, Michael C; Sun, Qi; Daniels, R Nathan; Camper, DeMarco; Kennedy, J Phillip; Phan, Jason; Olejniczak, Edward T; Lee, Taekyu; Waterson, Alex G; Rossanese, Olivia W; Fesik, Stephen W

    2014-03-04

    Aberrant activation of the small GTPase Ras by oncogenic mutation or constitutively active upstream receptor tyrosine kinases results in the deregulation of cellular signals governing growth and survival in ∼30% of all human cancers. However, the discovery of potent inhibitors of Ras has been difficult to achieve. Here, we report the identification of small molecules that bind to a unique pocket on the Ras:Son of Sevenless (SOS):Ras complex, increase the rate of SOS-catalyzed nucleotide exchange in vitro, and modulate Ras signaling pathways in cells. X-ray crystallography of Ras:SOS:Ras in complex with these molecules reveals that the compounds bind in a hydrophobic pocket in the CDC25 domain of SOS adjacent to the Switch II region of Ras. The structure-activity relationships exhibited by these compounds can be rationalized on the basis of multiple X-ray cocrystal structures. Mutational analyses confirmed the functional relevance of this binding site and showed it to be essential for compound activity. These molecules increase Ras-GTP levels and disrupt MAPK and PI3K signaling in cells at low micromolar concentrations. These small molecules represent tools to study the acute activation of Ras and highlight a pocket on SOS that may be exploited to modulate Ras signaling.

  9. Validation of the Chinese Version of the Sense of Self (SOS) Scale

    Science.gov (United States)

    King, Ronnel B.; Ganotice, Fraide A., Jr.; Watkins, David A.

    2012-01-01

    This study explored the cross-cultural applicability of the Sense of Self (SOS) Scale in the Hong Kong Chinese cultural context. The SOS Scale is a 26-item questionnaire designed to measure students' sense of purpose, self-reliance, and self-concept in school. Six hundred ninety-seven Hong Kong Chinese high school students participated in the…

  10. Quantitative learning strategies based on word networks

    Science.gov (United States)

    Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

    2018-02-01

    Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

  11. Functional consequences of inducible genetic elements from the p53 SOS response in a mammalian organ system.

    Science.gov (United States)

    Guthrie, O'neil W

    2017-10-01

    In response to DNA damage from ultraviolet (UV) radiation, bacteria deploy the SOS response in order to limit cell death. This bacterial SOS response is characterized by an increase in the recA gene that transactivates expression of multiple DNA repair genes. The current series of experiments demonstrate that a mammalian organ system (the cochlea) that is not evolutionarily conditioned to UV radiation can elicit SOS responses that are reminiscent of that of bacteria. This mammalian SOS response is characterized by an increase in the p53 gene with activation of multiple DNA repair genes that harbor p53 response elements in their promoters. Furthermore, the experimental results provide support for the notion of a convergent trigger paradox, where independent SOS triggers facilitate disparate physiologic sequelae (loss vs. recovery of function). Therefore, it is proposed that the mammalian SOS response is multifunctional and manipulation of this endogenous response could be exploited in future biomedical interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Identification of a novel streptococcal gene cassette mediating SOS mutagenesis in Streptococcus uberis

    NARCIS (Netherlands)

    Varhimo, Emilia; Savijoki, Kirsi; Jalava, Jari; Kuipers, Oscar P.; Varmanen, Pekka

    Streptococci have been considered to lack the classical SOS response, defined by increased mutation after UV exposure and regulation by LexA. Here we report the identification of a potential self-regulated SOS mutagenesis gene cassette in the Streptococcaceae family. Exposure to UV light was found

  13. Distributed Extreme Learning Machine for Nonlinear Learning over Network

    Directory of Open Access Journals (Sweden)

    Songyan Huang

    2015-02-01

    Full Text Available Distributed data collection and analysis over a network are ubiquitous, especially over a wireless sensor network (WSN. To our knowledge, the data model used in most of the distributed algorithms is linear. However, in real applications, the linearity of systems is not always guaranteed. In nonlinear cases, the single hidden layer feedforward neural network (SLFN with radial basis function (RBF hidden neurons has the ability to approximate any continuous functions and, thus, may be used as the nonlinear learning system. However, confined by the communication cost, using the distributed version of the conventional algorithms to train the neural network directly is usually prohibited. Fortunately, based on the theorems provided in the extreme learning machine (ELM literature, we only need to compute the output weights of the SLFN. Computing the output weights itself is a linear learning problem, although the input-output mapping of the overall SLFN is still nonlinear. Using the distributed algorithmto cooperatively compute the output weights of the SLFN, we obtain a distributed extreme learning machine (dELM for nonlinear learning in this paper. This dELM is applied to the regression problem and classification problem to demonstrate its effectiveness and advantages.

  14. Language Choice & Global Learning Networks

    Directory of Open Access Journals (Sweden)

    Dennis Sayers

    1995-05-01

    Full Text Available How can other languages be used in conjunction with English to further intercultural and multilingual learning when teachers and students participate in computer-based global learning networks? Two portraits are presented of multilingual activities in the Orillas and I*EARN learning networks, and are discussed as examples of the principal modalities of communication employed in networking projects between distant classes. Next, an important historical precedent --the social controversy which accompanied the introduction of telephone technology at the end of the last century-- is examined in terms of its implications for language choice in contemporary classroom telecomputing projects. Finally, recommendations are offered to guide decision making concerning the role of language choice in promoting collaborative critical inquiry.

  15. Learning Networks Distributed Environment

    NARCIS (Netherlands)

    Martens, Harrie; Vogten, Hubert; Koper, Rob; Tattersall, Colin; Van Rosmalen, Peter; Sloep, Peter; Van Bruggen, Jan; Spoelstra, Howard

    2005-01-01

    Learning Networks Distributed Environment is a prototype of an architecture that allows the sharing and modification of learning materials through a number of transport protocols. The prototype implements a p2p protcol using JXTA.

  16. Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

    CERN Document Server

    Hu, Fei

    2012-01-01

    Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

  17. The SOS response increases bacterial fitness, but not evolvability, under a sublethal dose of antibiotic.

    Science.gov (United States)

    Torres-Barceló, Clara; Kojadinovic, Mila; Moxon, Richard; MacLean, R Craig

    2015-10-07

    Exposure to antibiotics induces the expression of mutagenic bacterial stress-response pathways, but the evolutionary benefits of these responses remain unclear. One possibility is that stress-response pathways provide a short-term advantage by protecting bacteria against the toxic effects of antibiotics. Second, it is possible that stress-induced mutagenesis provides a long-term advantage by accelerating the evolution of resistance. Here, we directly measure the contribution of the Pseudomonas aeruginosa SOS pathway to bacterial fitness and evolvability in the presence of sublethal doses of ciprofloxacin. Using short-term competition experiments, we demonstrate that the SOS pathway increases competitive fitness in the presence of ciprofloxacin. Continued exposure to ciprofloxacin results in the rapid evolution of increased fitness and antibiotic resistance, but we find no evidence that SOS-induced mutagenesis accelerates the rate of adaptation to ciprofloxacin during a 200 generation selection experiment. Intriguingly, we find that the expression of the SOS pathway decreases during adaptation to ciprofloxacin, and this helps to explain why this pathway does not increase long-term evolvability. Furthermore, we argue that the SOS pathway fails to accelerate adaptation to ciprofloxacin because the modest increase in the mutation rate associated with SOS mutagenesis is offset by a decrease in the effective strength of selection for increased resistance at a population level. Our findings suggest that the primary evolutionary benefit of the SOS response is to increase bacterial competitive ability, and that stress-induced mutagenesis is an unwanted side effect, and not a selected attribute, of this pathway. © 2015 The Authors.

  18. SOS score: an optimized score to screen acute stroke patients for obstructive sleep apnea.

    Science.gov (United States)

    Camilo, Millene R; Sander, Heidi H; Eckeli, Alan L; Fernandes, Regina M F; Dos Santos-Pontelli, Taiza E G; Leite, Joao P; Pontes-Neto, Octavio M

    2014-09-01

    Obstructive sleep apnea (OSA) is frequent in acute stroke patients, and has been associated with higher mortality and worse prognosis. Polysomnography (PSG) is the gold standard diagnostic method for OSA, but it is impracticable as a routine for all acute stroke patients. We evaluated the accuracy of two OSA screening tools, the Berlin Questionnaire (BQ), and the Epworth Sleepiness Scale (ESS) when administered to relatives of acute stroke patients; we also compared these tools against a combined screening score (SOS score). Ischemic stroke patients were submitted to a full PSG at the first night after onset of symptoms. OSA severity was measured by apnea-hypopnea index (AHI). BQ and ESS were administered to relatives of stroke patients before the PSG and compared to SOS score for accuracy and C-statistics. We prospectively studied 39 patients. OSA (AHI ≥10/h) was present in 76.9%. The SOS score [area under the curve (AUC): 0.812; P = 0.005] and ESS (AUC: 0.789; P = 0.009) had good predictive value for OSA. The SOS score was the only tool with significant predictive value (AUC: 0.686; P = 0.048) for severe OSA (AHI ≥30/h), when compared to ESS (P = 0.119) and BQ (P = 0.191). The threshold of SOS ≤10 showed high sensitivity (90%) and negative predictive value (96.2%) for OSA; SOS ≥20 showed high specificity (100%) and positive predictive value (92.5%) for severe OSA. The SOS score administered to relatives of stroke patients is a useful tool to screen for OSA and may decrease the need for PSG in acute stroke setting. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Induction of the SOS system in Escherichia coli after UVA (320 - 400 nm) irradiation

    International Nuclear Information System (INIS)

    Batbyamba, G.; Drasil, V.

    1988-01-01

    Induction of the SOS repair system in E. coli caused by broad-band (320 - 400 nm) UVA radiation and an oxygen effect in this induction were studied using the sfiA::lacZ operon fusion. Moreover, an oxygen effect on the broad-band UVA radiation-induced cell killing was studied. The experiments indicate that: (1) Broad-band UVA light can produce lethal damage to cells as well as DNA damage able to generate an SOS-inducing signal. This damage is O 2 -dependent to a significant extent: SOSIP (O 2 )/ SOSIP (Ar) = 1.61 and OER = 1.96; (2) After UVA irradiation the SOS induction factor increases monotonously in the time interval longer than 4 h indicating that the SOS-inducing DNA damage caused by UVA irradiation has a 'long-lived' character; (3) Oxic and hypoxic incubation following UVA irradiation carried out under aerobic and anaerobic conditions resulted in a strong oxygen effect: SOSIP(O 2 )/SOSIP(Ar) ∼ 5. On the basis of these results and literary data it was concluded that one of the main toxic photoproducts formed as a result of UVA irradiation of the cells in a culture medium might be hydrogen peroxide (H 2 O 2 ). H 2 O 2 decays gradually during post-irradiation incubation and yields reactive radical species, mainly OH radical, that result in a formation of SOS-inducing DNA damages and contribute to cell lethality, and prolonged SOS induction. (author)

  20. Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

    Directory of Open Access Journals (Sweden)

    Chernoded Andrey

    2017-01-01

    Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

  1. SOS Children's Friendly Community Historical Overview

    Science.gov (United States)

    Lukaš, Mirko; Lenard, Ivan

    2014-01-01

    SOS Children's Village Croatia is categorized as a children's home whose primary goal is taking care of children without an adequate parental care or parents themselves. Moreover, it aims at providing children, regardless of their racial, national or religious affiliation, with affection and love in a safe family environment. In addition, SOS…

  2. Learning and coding in biological neural networks

    Science.gov (United States)

    Fiete, Ila Rani

    How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and

  3. Collective Learning in Games through Social Networks

    NARCIS (Netherlands)

    Kosterman, S.; Gierasimczuk, N.; Armentano, M.G.; Monteserin, A.; Tang, J.; Yannibelli, V.

    2015-01-01

    This paper argues that combining social networks communication and games can positively influence the learning behavior of players. We propose a computational model that combines features of social network learning (communication) and game-based learning (strategy reinforcement). The focus is on

  4. A metabonomic evaluation of the monocrotaline-induced sinusoidal obstruction syndrome (SOS) in rats

    International Nuclear Information System (INIS)

    Conotte, R.; Colet, J.-M.

    2014-01-01

    The main curative treatment of colorectal cancer remains the surgery. However, when metastases are suspected, surgery is followed by a preventive chemotherapy using oxaliplatin which, unfortunately, may cause liver sinusoidal obstruction syndrome (SOS). Such hepatic damage is barely detected during or after chemotherapy due to a lack of effective diagnostic procedures, but liver biopsy. The primary objective of the present study was to identify potential early diagnosis biomarkers of SOS using a metabonomic approach. SOS was induced in rats by monocrotaline, a prototypical toxic substance. 1 H NMR spectroscopy analysis of urine samples collected from rats treated with monocrotaline showed significant metabolic changes as compared to controls. During a first phase, cellular protective mechanisms such as an increased synthesis of GSH (reduced taurine) and the recruitment of cell osmolytes in the liver (betaine) were seen. In the second phase, the disturbance of the urea cycle (increased ornithine and urea reduction) leading to the depletion of NO, the alteration in the GSH synthesis (increased creatine and GSH precursors (glutamate, dimethylglycine and sarcosine)), and the liver necrosis (decrease taurine and increase creatine) all indicate the development of SOS. - Highlights: • Urine metabonomic profiles of SOS have been identified. • Urine osmoprotectants and anti-oxidants indicated an initial liver protection. • Liver necrosis was demonstrated by increased urine levels of taurine and creatine. • NO depletion was suggested by changes in ornithine and urea

  5. Atomic orbital-based SOS-MP2 with tensor hypercontraction. II. Local tensor hypercontraction

    Science.gov (United States)

    Song, Chenchen; Martínez, Todd J.

    2017-01-01

    In the first paper of the series [Paper I, C. Song and T. J. Martinez, J. Chem. Phys. 144, 174111 (2016)], we showed how tensor-hypercontracted (THC) SOS-MP2 could be accelerated by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs). This reduced the formal scaling of the SOS-MP2 energy calculation to cubic with respect to system size. The computational bottleneck then becomes the THC metric matrix inversion, which scales cubically with a large prefactor. In this work, the local THC approximation is proposed to reduce the computational cost of inverting the THC metric matrix to linear scaling with respect to molecular size. By doing so, we have removed the primary bottleneck to THC-SOS-MP2 calculations on large molecules with O(1000) atoms. The errors introduced by the local THC approximation are less than 0.6 kcal/mol for molecules with up to 200 atoms and 3300 basis functions. Together with the graphical processing unit techniques and locality-exploiting approaches introduced in previous work, the scaled opposite spin MP2 (SOS-MP2) calculations exhibit O(N2.5) scaling in practice up to 10 000 basis functions. The new algorithms make it feasible to carry out SOS-MP2 calculations on small proteins like ubiquitin (1231 atoms/10 294 atomic basis functions) on a single node in less than a day.

  6. Onderzoek naar de toepasbaarheid van SOS-chromotest

    NARCIS (Netherlands)

    Voogd CE; van der Stel JJ; Verharen HW; van Bruchem MC

    1988-01-01

    Met 35 stoffen werd de mutagene activiteit onderzocht met een SOS-chromotest kit, de Ames-test en de fluctuatietest met Klebsiella pneumoniae. Voorzover het alkylerende stoffen betreft die basenpaar substituties veroorzaken, blijkt er een goede overeenstemming te bestaan met de resultaten van

  7. Survival and SOS response induction in ultraviolet B irradiated Escherichia coli cells with defective repair mechanisms.

    Science.gov (United States)

    Prada Medina, Cesar Augusto; Aristizabal Tessmer, Elke Tatjana; Quintero Ruiz, Nathalia; Serment-Guerrero, Jorge; Fuentes, Jorge Luis

    2016-06-01

    Purpose In this paper, the contribution of different genes involved in DNA repair for both survival and SOS induction in Escherichia coli mutants exposed to ultraviolet B radiation (UVB, [wavelength range 280-315 nm]) was evaluated. Materials and methods E. coli strains defective in uvrA, oxyR, recO, recN, recJ, exoX, recB, recD or xonA genes were used to determine cell survival. All strains also had the genetic sulA::lacZ fusion, which allowed for the quantification of SOS induction through the SOS Chromotest. Results Five gene products were particularly important for survival, as follows: UvrA > RecB > RecO > RecJ > XonA. Strains defective in uvrA and recJ genes showed elevated SOS induction compared with the wild type, which remained stable for up to 240 min after UVB-irradiation. In addition, E. coli strains carrying the recO or recN mutation showed no SOS induction. Conclusions The nucleotide excision and DNA recombination pathways were equally used to repair UVB-induced DNA damage in E. coli cells. The sulA gene was not turned off in strains defective in UvrA and RecJ. RecO protein was essential for processing DNA damage prior to SOS induction. In this study, the roles of DNA repair proteins and their contributions to the mechanisms that induce SOS genes in E. coli are proposed.

  8. Supervised Learning with Complex-valued Neural Networks

    CERN Document Server

    Suresh, Sundaram; Savitha, Ramasamy

    2013-01-01

    Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks.  Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computati...

  9. Changing Conditions for Networked Learning?

    DEFF Research Database (Denmark)

    Ryberg, Thomas

    2011-01-01

    in describing the novel pedagogical potentials of these new technologies and practices (e.g. in debates around virtual learning environments versus personal learning environment). Likewise, I shall briefly discuss the notions of ‘digital natives’ or ‘the net generation’ from a critical perspective...... of social technologies. I argue that we are seeing the emergence of new architectures and scales of participation, collaboration and networking e.g. through interesting formations of learning networks at different levels of scale, for different purposes and often bridging boundaries such as formal...

  10. Learning-parameter adjustment in neural networks

    Science.gov (United States)

    Heskes, Tom M.; Kappen, Bert

    1992-06-01

    We present a learning-parameter adjustment algorithm, valid for a large class of learning rules in neural-network literature. The algorithm follows directly from a consideration of the statistics of the weights in the network. The characteristic behavior of the algorithm is calculated, both in a fixed and a changing environment. A simple example, Widrow-Hoff learning for statistical classification, serves as an illustration.

  11. Researching Design, Experience and Practice of Networked Learning

    DEFF Research Database (Denmark)

    Hodgson, Vivien; de Laat, Maarten; McConnell, David

    2014-01-01

    and final section draws attention to a growing topic of interest within networked learning: that of networked learning in informal practices. In addition, we provide a reflection on the theories, methods and settings featured in the networked learning research of the chapters. We conclude the introduction...

  12. Influence of the gene xthA in the activation of SOS response of Escherichia coli

    International Nuclear Information System (INIS)

    Dominguez M, V.

    2013-01-01

    The SOS response is one of the strategies that has Escherichia coli to counteract the lesions in the genetic material. The response is integrated for approximately 60 genes that when are activated they provide to the cell a bigger opportunity to survive. For the activation of this system is necessary that DNA regions of simple chain are generated, in such a way that most of the lesions should be processed, to be able to induce this answer. Some genes that intervene in this procedure, as recO, recB and recJ are recognized since when being exposed to the radiation, their activity SOS is smaller than in a wild strain. In previous works has been studied that to inactivate the genes that are involves in the lesions processing to generate DNA of simple chain, the SOS induction level diminishes with regard to a wild strain, but that when eliminating the genes that are involves directly in the repair, the SOS response increases. In this work a strain with defects in the gene xthA was built, which encodes for an endonuclease AP that participates in the repair mechanism by base excision and was evaluated their sensibility as the activity of the SOS response when exposing it to UV light and gamma radiation. The results showed that the lethality of the strain with the defect is very similar to the wild strain; while the activation level of the SOS response is bigger in comparison with the wild strain when being exposed to UV light; suggesting the existence of an enzyme that recognizes the lesions that produces this radiation, however, is not this the main repair channel, since the survival is similar to that of the wild strain. On the contrary, the results obtained with gamma radiation showed that the lethality diminishes in comparison to that of the wild strain, like the SOS activity; due surely to that the gene product intervenes in the repair for base excision, participating in the formation of the previous substrate to the activation of the SOS response. (Author)

  13. Mechanism of SOS PR-domain autoinhibition revealed by single-molecule assays on native protein from lysate.

    Science.gov (United States)

    Lee, Young Kwang; Low-Nam, Shalini T; Chung, Jean K; Hansen, Scott D; Lam, Hiu Yue Monatrice; Alvarez, Steven; Groves, Jay T

    2017-04-28

    The guanine nucleotide exchange factor (GEF) Son of Sevenless (SOS) plays a critical role in signal transduction by activating Ras. Here we introduce a single-molecule assay in which individual SOS molecules are captured from raw cell lysate using Ras-functionalized supported membrane microarrays. This enables characterization of the full-length SOS protein, which has not previously been studied in reconstitution due to difficulties in purification. Our measurements on the full-length protein reveal a distinct role of the C-terminal proline-rich (PR) domain to obstruct the engagement of allosteric Ras independently of the well-known N-terminal domain autoinhibition. This inhibitory role of the PR domain limits Grb2-independent recruitment of SOS to the membrane through binding of Ras·GTP in the SOS allosteric binding site. More generally, this assay strategy enables characterization of the functional behaviour of GEFs with single-molecule precision but without the need for purification.

  14. Learning Bayesian networks for discrete data

    KAUST Repository

    Liang, Faming

    2009-02-01

    Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.

  15. A plasmid-encoded UmuD homologue regulates expression of Pseudomonas aeruginosa SOS genes.

    Science.gov (United States)

    Díaz-Magaña, Amada; Alva-Murillo, Nayeli; Chávez-Moctezuma, Martha P; López-Meza, Joel E; Ramírez-Díaz, Martha I; Cervantes, Carlos

    2015-07-01

    The Pseudomonas aeruginosa plasmid pUM505 contains the umuDC operon that encodes proteins similar to error-prone repair DNA polymerase V. The umuC gene appears to be truncated and its product is probably not functional. The umuD gene, renamed umuDpR, possesses an SOS box overlapped with a Sigma factor 70 type promoter; accordingly, transcriptional fusions revealed that the umuDpR gene promoter is activated by mitomycin C. The predicted sequence of the UmuDpR protein displays 23 % identity with the Ps. aeruginosa SOS-response LexA repressor. The umuDpR gene caused increased MMC sensitivity when transferred to the Ps. aeruginosa PAO1 strain. As expected, PAO1-derived knockout lexA-  mutant PW6037 showed resistance to MMC; however, when the umuDpR gene was transferred to PW6037, MMC resistance level was reduced. These data suggested that UmuDpR represses the expression of SOS genes, as LexA does. To test whether UmuDpR exerts regulatory functions, expression of PAO1 SOS genes was evaluated by reverse transcription quantitative PCR assays in the lexA-  mutant with or without the pUC_umuD recombinant plasmid. Expression of lexA, imuA and recA genes increased 3.4-5.3 times in the lexA-  mutant, relative to transcription of the corresponding genes in the lexA+ strain, but decreased significantly in the lexA- /umuDpR transformant. These results confirmed that the UmuDpR protein is a repressor of Ps. aeruginosa SOS genes controlled by LexA. Electrophoretic mobility shift assays, however, did not show binding of UmuDpR to 5' regions of SOS genes, suggesting an indirect mechanism of regulation.

  16. Genotoxicity risk assessment of diversely substituted quinolines using the SOS chromotest.

    Science.gov (United States)

    Duran, Leidy Tatiana Díaz; Rincón, Nathalia Olivar; Galvis, Carlos Eduardo Puerto; Kouznetsov, Vladimir V; Lorenzo, Jorge Luis Fuentes

    2015-03-01

    Quinolines are aromatic nitrogen compounds with wide therapeutic potential to treat parasitic and microbial diseases. In this study, the genotoxicity of quinoline, 4-methylquinoline, 4-nitroquinoline-1-oxide (4-NQO), and diversely functionalized quinoline derivatives and the influence of the substituents (functional groups and/or atoms) on their genotoxicity were tested using the SOS chromotest. Quinoline derivatives that induce genotoxicity by the formation of an enamine epoxide structure did not induce the SOS response in Escherichia coli PQ37 cells, with the exception of 4-methylquinoline that was weakly genotoxic. The chemical nature of the substitution (C-5 to C-8: hydroxyl, nitro, methyl, isopropyl, chlorine, fluorine, and iodine atoms; C-2: phenyl and 3,4-methylenedioxyphenyl rings) of quinoline skeleton did not significantly modify compound genotoxicities; however, C-2 substitution with α-, β-, or γ-pyridinyl groups removed 4-methylquinoline genotoxicity. On the other hand, 4-NQO derivatives whose genotoxic mechanism involves reduction of the C-4 nitro group were strong inducers of the SOS response. Methyl and nitrophenyl substituents at C-2 of 4-NQO core affected the genotoxic potency of this molecule. The relevance of these results is discussed in relation to the potential use of the substituted quinolines. The work showed the sensitivity of SOS chromotest for studying structure-genotoxicity relationships and bioassay-guided quinoline synthesis. © 2013 Wiley Periodicals, Inc.

  17. Endovascular stentectomy using the snare over stent-retriever (SOS technique: An experimental feasibility study.

    Directory of Open Access Journals (Sweden)

    Tareq Meyer

    Full Text Available Feasibility of endovascular stentectomy using a snare over stent-retriever (SOS technique was evaluated in a silicon flow model and an in vivo swine model. In vitro, stentectomy of different intracranial stents using the SOS technique was feasible in 22 out of 24 (92% retrieval maneuvers. In vivo, stentectomy was successful in 10 out of 10 procedures (100%. In one case self-limiting vasospasm was observed angiographically as a technique related complication in the animal model. Endovascular stentectomy using the SOS technique is feasible in an experimental setting and may be transferred to a clinical scenario.

  18. Learning network theory : its contribution to our understanding of work-based learning projects and learning climate

    NARCIS (Netherlands)

    Poell, R.F.; Moorsel, M.A.A.H. van

    1996-01-01

    This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of

  19. Sos - response induction by gamma radiation in Escherichia coli strains with different repair capacities

    International Nuclear Information System (INIS)

    Serment Guerrero, J.H.

    1992-01-01

    The Sos - response in Escherichia coli is formed by several genes involved in mechanisms of tolerance and/or repair, and only activates when a DNA - damage appears. It is controlled by recA and lexA genes. In normal circumstances, LexA protein is linked in every Sos operators, blocking the transcription. When a DNA damage occurs, a Sos signal is generated, Rec A protein changes its normal functions, starts acting as a protease and cleaves Lex A, allowing the transcription of all Sos genes. This response can be quantified by means of Sos Chromo test, performed by Quillardet and Ofnung (1985). In using the Chromo test, it has been observed that the DNA damage made by gamma radiation in Escherichia coli depends on both the doses and the doses rate. It has been shown that the exposure of Escherichia coli PQ37 strain (uvrA) to low doses at low dose rate appears to retard the response, suggesting the action of a repair mechanism. (Brena 1990). In this work, we compare the response in Escherichia coli strains deficient in different mechanisms of repair and/or tolerance. It is observed the importance of rec N gene in the repair of DNA damage produced by gamma radiation. (Author)

  20. Cooperative Learning for Distributed In-Network Traffic Classification

    Science.gov (United States)

    Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

    2017-04-01

    Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

  1. Monitoring Ras Interactions with the Nucleotide Exchange Factor Son of Sevenless (Sos) Using Site-specific NMR Reporter Signals and Intrinsic Fluorescence*

    Science.gov (United States)

    Vo, Uybach; Vajpai, Navratna; Flavell, Liz; Bobby, Romel; Breeze, Alexander L.; Embrey, Kevin J.; Golovanov, Alexander P.

    2016-01-01

    The activity of Ras is controlled by the interconversion between GTP- and GDP-bound forms partly regulated by the binding of the guanine nucleotide exchange factor Son of Sevenless (Sos). The details of Sos binding, leading to nucleotide exchange and subsequent dissociation of the complex, are not completely understood. Here, we used uniformly 15N-labeled Ras as well as [13C]methyl-Met,Ile-labeled Sos for observing site-specific details of Ras-Sos interactions in solution. Binding of various forms of Ras (loaded with GDP and mimics of GTP or nucleotide-free) at the allosteric and catalytic sites of Sos was comprehensively characterized by monitoring signal perturbations in the NMR spectra. The overall affinity of binding between these protein variants as well as their selected functional mutants was also investigated using intrinsic fluorescence. The data support a positive feedback activation of Sos by Ras·GTP with Ras·GTP binding as a substrate for the catalytic site of activated Sos more weakly than Ras·GDP, suggesting that Sos should actively promote unidirectional GDP → GTP exchange on Ras in preference of passive homonucleotide exchange. Ras·GDP weakly binds to the catalytic but not to the allosteric site of Sos. This confirms that Ras·GDP cannot properly activate Sos at the allosteric site. The novel site-specific assay described may be useful for design of drugs aimed at perturbing Ras-Sos interactions. PMID:26565026

  2. Overexpression of the PtSOS2 gene improves tolerance to salt stress in transgenic poplar plants.

    Science.gov (United States)

    Yang, Yang; Tang, Ren-Jie; Jiang, Chun-Mei; Li, Bei; Kang, Tao; Liu, Hua; Zhao, Nan; Ma, Xu-Jun; Yang, Lei; Chen, Shao-Liang; Zhang, Hong-Xia

    2015-09-01

    In higher plants, the salt overly sensitive (SOS) signalling pathway plays a crucial role in maintaining ion homoeostasis and conferring salt tolerance under salinity condition. Previously, we functionally characterized the conserved SOS pathway in the woody plant Populus trichocarpa. In this study, we demonstrate that overexpression of the constitutively active form of PtSOS2 (PtSOS2TD), one of the key components of this pathway, significantly increased salt tolerance in aspen hybrid clone Shanxin Yang (Populus davidiana × Populus bolleana). Compared to the wild-type control, transgenic plants constitutively expressing PtSOS2TD exhibited more vigorous growth and produced greater biomass in the presence of high concentrations of NaCl. The improved salt tolerance was associated with a decreased Na(+) accumulation in the leaves of transgenic plants. Further analyses revealed that plasma membrane Na(+) /H(+) exchange activity and Na(+) efflux in transgenic plants were significantly higher than those in the wild-type plants. Moreover, transgenic plants showed improved capacity in scavenging reactive oxygen species (ROS) generated by salt stress. Taken together, our results suggest that PtSOS2 could serve as an ideal target gene to genetically engineer salt-tolerant trees. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  3. 77 FR 65896 - Award of a Single-Source Replacement Grant to SOS Children's Villages Illinois in Chicago, IL

    Science.gov (United States)

    2012-10-31

    ....623] Award of a Single-Source Replacement Grant to SOS Children's Villages Illinois in Chicago, IL... (FYSB) announces the award of a single-source replacement grant to SOS Children's Villages Illinois in... grant. ACYF/FYSB has designated SOS Children's Villages Illinois, a 501(c)(3) non-profit organization...

  4. Distance learning, problem based learning and dynamic knowledge networks.

    Science.gov (United States)

    Giani, U; Martone, P

    1998-06-01

    This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.

  5. A Team Formation and Project-based Learning Support Service for Social Learning Networks

    NARCIS (Netherlands)

    Spoelstra, Howard; Van Rosmalen, Peter; Van de Vrie, Evert; Obreza, Matija; Sloep, Peter

    2014-01-01

    The Internet affords new approaches to learning. Geographically dispersed self-directed learners can learn in computer-supported communities, forming social learning networks. However, self-directed learners can suffer from a lack of continuous motivation. And surprisingly, social learning networks

  6. Contingent factors affecting network learning

    OpenAIRE

    Peters, Linda D.; Pressey, Andrew D.; Johnston, Wesley J.

    2016-01-01

    To increase understanding of the impact of individuals on organizational learning processes, this paper explores the impact of individual cognition and action on the absorptive capacity process of the wider network. In particular this study shows how contingent factors such as social integration mechanisms and power relationships influence how network members engage in, and benefit from, learning. The use of cognitive consistency and sensemaking theory enables examination of how these conting...

  7. A metabonomic evaluation of the monocrotaline-induced sinusoidal obstruction syndrome (SOS) in rats

    Energy Technology Data Exchange (ETDEWEB)

    Conotte, R.; Colet, J.-M., E-mail: jean-marie.colet@umons.ac.be

    2014-04-15

    The main curative treatment of colorectal cancer remains the surgery. However, when metastases are suspected, surgery is followed by a preventive chemotherapy using oxaliplatin which, unfortunately, may cause liver sinusoidal obstruction syndrome (SOS). Such hepatic damage is barely detected during or after chemotherapy due to a lack of effective diagnostic procedures, but liver biopsy. The primary objective of the present study was to identify potential early diagnosis biomarkers of SOS using a metabonomic approach. SOS was induced in rats by monocrotaline, a prototypical toxic substance. {sup 1}H NMR spectroscopy analysis of urine samples collected from rats treated with monocrotaline showed significant metabolic changes as compared to controls. During a first phase, cellular protective mechanisms such as an increased synthesis of GSH (reduced taurine) and the recruitment of cell osmolytes in the liver (betaine) were seen. In the second phase, the disturbance of the urea cycle (increased ornithine and urea reduction) leading to the depletion of NO, the alteration in the GSH synthesis (increased creatine and GSH precursors (glutamate, dimethylglycine and sarcosine)), and the liver necrosis (decrease taurine and increase creatine) all indicate the development of SOS. - Highlights: • Urine metabonomic profiles of SOS have been identified. • Urine osmoprotectants and anti-oxidants indicated an initial liver protection. • Liver necrosis was demonstrated by increased urine levels of taurine and creatine. • NO depletion was suggested by changes in ornithine and urea.

  8. Effect of the SOS response on the mean fitness of unicellular populations: a quasispecies approach.

    Science.gov (United States)

    Kama, Amit; Tannenbaum, Emmanuel

    2010-11-30

    The goal of this paper is to develop a mathematical model that analyzes the selective advantage of the SOS response in unicellular organisms. To this end, this paper develops a quasispecies model that incorporates the SOS response. We consider a unicellular, asexually replicating population of organisms, whose genomes consist of a single, double-stranded DNA molecule, i.e. one chromosome. We assume that repair of post-replication mismatched base-pairs occurs with probability , and that the SOS response is triggered when the total number of mismatched base-pairs is at least . We further assume that the per-mismatch SOS elimination rate is characterized by a first-order rate constant . For a single fitness peak landscape where the master genome can sustain up to mismatches and remain viable, this model is analytically solvable in the limit of infinite sequence length. The results, which are confirmed by stochastic simulations, indicate that the SOS response does indeed confer a fitness advantage to a population, provided that it is only activated when DNA damage is so extensive that a cell will die if it does not attempt to repair its DNA.

  9. Dynamic studies of H-Ras•GTPγS interactions with nucleotide exchange factor Sos reveal a transient ternary complex formation in solution.

    Science.gov (United States)

    Vo, Uybach; Vajpai, Navratna; Embrey, Kevin J; Golovanov, Alexander P

    2016-07-14

    The cycling between GDP- and GTP- bound forms of the Ras protein is partly regulated by the binding of Sos. The structural/dynamic behavior of the complex formed between activated Sos and Ras at the point of the functional cycle where the nucleotide exchange is completed has not been described to date. Here we show that solution NMR spectra of H-Ras∙GTPγS mixed with a functional fragment of Sos (Sos(Cat)) at a 2:1 ratio are consistent with the formation of a rather dynamic assembly. H-Ras∙GTPγS binding was in fast exchange on the NMR timescale and retained a significant degree of molecular tumbling independent of Sos(Cat), while Sos(Cat) also tumbled largely independently of H-Ras. Estimates of apparent molecular weight from both NMR data and SEC-MALS revealed that, at most, only one H-Ras∙GTPγS molecule appears stably bound to Sos. The weak transient interaction between Sos and the second H-Ras∙GTPγS may provide a necessary mechanism for complex dissociation upon the completion of the native GDP → GTP exchange reaction, but also explains measurable GTP → GTP exchange activity of Sos routinely observed in in vitro assays that use fluorescently-labelled analogs of GTP. Overall, the data presents the first dynamic snapshot of Ras functional cycle as controlled by Sos.

  10. Learning network theory : its contribution to our understanding of work-based learning projects and learning climate

    OpenAIRE

    Poell, R.F.; Moorsel, M.A.A.H. van

    1996-01-01

    This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of learning groups in organisations. Four theoretical types of learning projects are distinguished. Four different approaches to the learning climate of work groups are compared to the approach offered by t...

  11. Monitoring Ras Interactions with the Nucleotide Exchange Factor Son of Sevenless (Sos) Using Site-specific NMR Reporter Signals and Intrinsic Fluorescence.

    Science.gov (United States)

    Vo, Uybach; Vajpai, Navratna; Flavell, Liz; Bobby, Romel; Breeze, Alexander L; Embrey, Kevin J; Golovanov, Alexander P

    2016-01-22

    The activity of Ras is controlled by the interconversion between GTP- and GDP-bound forms partly regulated by the binding of the guanine nucleotide exchange factor Son of Sevenless (Sos). The details of Sos binding, leading to nucleotide exchange and subsequent dissociation of the complex, are not completely understood. Here, we used uniformly (15)N-labeled Ras as well as [(13)C]methyl-Met,Ile-labeled Sos for observing site-specific details of Ras-Sos interactions in solution. Binding of various forms of Ras (loaded with GDP and mimics of GTP or nucleotide-free) at the allosteric and catalytic sites of Sos was comprehensively characterized by monitoring signal perturbations in the NMR spectra. The overall affinity of binding between these protein variants as well as their selected functional mutants was also investigated using intrinsic fluorescence. The data support a positive feedback activation of Sos by Ras·GTP with Ras·GTP binding as a substrate for the catalytic site of activated Sos more weakly than Ras·GDP, suggesting that Sos should actively promote unidirectional GDP → GTP exchange on Ras in preference of passive homonucleotide exchange. Ras·GDP weakly binds to the catalytic but not to the allosteric site of Sos. This confirms that Ras·GDP cannot properly activate Sos at the allosteric site. The novel site-specific assay described may be useful for design of drugs aimed at perturbing Ras-Sos interactions. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  12. Learning and structure of neuronal networks

    Indian Academy of Sciences (India)

    We study the effect of learning dynamics on network topology. Firstly, a network of discrete dynamical systems is considered for this purpose and the coupling strengths are made to evolve according to a temporal learning rule that is based on the paradigm of spike-time-dependent plasticity (STDP). This incorporates ...

  13. Stochastic Variational Learning in Recurrent Spiking Networks

    Directory of Open Access Journals (Sweden)

    Danilo eJimenez Rezende

    2014-04-01

    Full Text Available The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

  14. Stochastic variational learning in recurrent spiking networks.

    Science.gov (United States)

    Jimenez Rezende, Danilo; Gerstner, Wulfram

    2014-01-01

    The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators) conveying information about "novelty" on a statistically rigorous ground. Simulations show that our model is able to learn both stationary and non-stationary patterns of spike trains. We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

  15. Suppressive effects of coffee on the SOS responses induced by UV and chemical mutagens

    International Nuclear Information System (INIS)

    Obana, Hirotaka; Nakamura, Sei-ichi; Tanaka, Ryou-ichi

    1986-01-01

    SOS-inducing activity of UV or chemical mutagens was strongly suppressed by instant coffee in Salmonella typhimurium TA1535/pSK1002. As decaffeinated instant coffee showed a similarly strong suppressive effect, it would seem that caffeine, a known inhibitor of SOS responses, is not responsible for the effect observed. The suppression was also shown by freshly brewed coffee extracts. However, the suppression was absent in green coffee-bean extracts. These results suggest that coffee contains some substance(s) which, apart from caffeine, suppresses SOS-inducing activity of UV or chemical mutagens and that the suppressive substance(s) are produced by roasting coffee beans. (Auth.)

  16. A Network of Resistances against a Multiple Crisis. SOS Rosarno and the Experimentation of Socio-Economic Alternative Models

    Directory of Open Access Journals (Sweden)

    Federico Oliveri

    2015-07-01

    Full Text Available SOS Rosarno was launched in 2011 by a group of small farmers and activists based in the Gioia Tauro Plain, Calabria, Southern Italy. The idea was to sell organic citrus fruits through short self-organized supply chains, essentially based on Solidarity Purchase Groups, in order to allow producers to pay migrant workers according to the law, to receive a fair remuneration, to guarantee healthy and affordable food to consumers, to protect the integrity of the environment. This paper aims to reconstruct the ideological frame and the genealogy, the organization and the practices, the impact and the limits of SOS Rosarno, drawing mainly on the political documents produced by the association and in-depth interviews with its diverse members. It clarifies, on one side, the strategies of alternative economy and the new social alliances implemented in order to challenge those conditions which impoverish small producers and let migrant farmworkers be exploited and become the target of racism in many Italian countrysides. It explores, on the other side, the development of a new peasant civilization as alternative to the current economic and environmental crises, in terms of de-commodification of nature and labour, construction of a convivial democratic society, transition from monoculture to food sovereignty.

  17. Viral and cellular SOS-regulated motor proteins: dsDNA translocation mechanisms with divergent functions.

    Science.gov (United States)

    Wolfe, Annie; Phipps, Kara; Weitao, Tao

    2014-01-01

    DNA damage attacks on bacterial cells have been known to activate the SOS response, a transcriptional response affecting chromosome replication, DNA recombination and repair, cell division and prophage induction. All these functions require double-stranded (ds) DNA translocation by ASCE hexameric motors. This review seeks to delineate the structural and functional characteristics of the SOS response and the SOS-regulated DNA translocases FtsK and RuvB with the phi29 bacteriophage packaging motor gp16 ATPase as a prototype to study bacterial motors. While gp16 ATPase, cellular FtsK and RuvB are similarly comprised of hexameric rings encircling dsDNA and functioning as ATP-driven DNA translocases, they utilize different mechanisms to accomplish separate functions, suggesting a convergent evolution of these motors. The gp16 ATPase and FtsK use a novel revolution mechanism, generating a power stroke between subunits through an entropy-DNA affinity switch and pushing dsDNA inward without rotation of DNA and the motor, whereas RuvB seems to employ a rotation mechanism that remains to be further characterized. While FtsK and RuvB perform essential tasks during the SOS response, their roles may be far more significant as SOS response is involved in antibiotic-inducible bacterial vesiculation and biofilm formation as well as the perspective of the bacteria-cancer evolutionary interaction.

  18. THE IMPACTS OF SOCIAL NETWORKING SITES IN HIGHER LEARNING

    Directory of Open Access Journals (Sweden)

    Mohd Ishak Bin Ismail

    2016-02-01

    Full Text Available Social networking sites, a web-based application have permeated the boundary between personal lives and student lives. Nowadays, students in higher learning used social networking site such as Facebook to facilitate their learning through the academic collaboration which it further enhances students’ social capital. Social networking site has many advantages to improve students’ learning. To date, Facebook is the leading social networking sites at this time which it being widely used by students in higher learning to communicate to each other, to carry out academic collaboration and sharing resources. Learning through social networking sites is based on the social interaction which learning are emphasizing on students, real world resources, active students` participation, diversity of learning resources and the use of digital tools to deliver meaningful learning. Many studies found the positive, neutral and negative impact of social networking sites on academic performance. Thus, this study will determine the relationship between Facebook usage and academic achievement. Also, it will investigate the association of social capital and academic collaboration to Facebook usage.

  19. Sensor Data from the NERACOOS SOS Server, 2000-present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) Sensor Observation Service (SOS) The OCEANS IE -- formally approved as an OGC...

  20. High-throughput screening identifies small molecules that bind to the RAS:SOS:RAS complex and perturb RAS signaling.

    Science.gov (United States)

    Burns, Michael C; Howes, Jennifer E; Sun, Qi; Little, Andrew J; Camper, DeMarco V; Abbott, Jason R; Phan, Jason; Lee, Taekyu; Waterson, Alex G; Rossanese, Olivia W; Fesik, Stephen W

    2018-05-01

    K-RAS is mutated in approximately 30% of human cancers, resulting in increased RAS signaling and tumor growth. Thus, RAS is a highly validated therapeutic target, especially in tumors of the pancreas, lung and colon. Although directly targeting RAS has proven to be challenging, it may be possible to target other proteins involved in RAS signaling, such as the guanine nucleotide exchange factor Son of Sevenless (SOS). We have previously reported on the discovery of small molecules that bind to SOS1, activate SOS-mediated nucleotide exchange on RAS, and paradoxically inhibit ERK phosphorylation (Burns et al., PNAS, 2014). Here, we describe the discovery of additional, structurally diverse small molecules that also bind to SOS1 in the same pocket and elicit similar biological effects. We tested >160,000 compounds in a fluorescence-based assay to assess their effects on SOS-mediated nucleotide exchange. X-Ray structures revealed that these small molecules bind to the CDC25 domain of SOS1. Compounds that elicited high levels of nucleotide exchange activity in vitro increased RAS-GTP levels in cells, and inhibited phospho ERK levels at higher treatment concentrations. The identification of structurally diverse SOS1 binding ligands may assist in the discovery of new molecules designed to target RAS-driven tumors. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. Physical modeling of SOS P channel MOSFET and comparison with bulk devices

    International Nuclear Information System (INIS)

    Merckel, G.; Gris, Y.

    1976-01-01

    The main technological steps applied to P channel MOSFET's on SOS are recalled. A large-signal model derived from a physical analysis is presented. Gate-source and gate-drain capacitors have been linearized versus drain voltage. Due to low injection, the only diffusion capacitance of the source-substrate forward biased diode, and the depletion capacitance of the drain-substrate reverse biased diode were taken into account. Some typical parameters measured on SOS and bulk devices are given [fr

  2. The Use Of Social Networking Sites For Learning In Institutions Of Higher Learning

    Directory of Open Access Journals (Sweden)

    Mange Gladys Nkatha

    2015-08-01

    Full Text Available Abstract Institutions of higher learning are facing greater challenges to change and subjected to various transformations in the surrounding environment including technology. These challenge and motivate them to explore new ways to improve their teaching approaches. This study sought to investigate the use of social networking site in institutions of higher learning. To this end two objectives were formulated 1 to investigate the current state of the use of social networking sites by the students 2 investigate how social networking sites can be used to promote authentic learning in institutions of higher learning. The study adopted exploratory approach using descriptive survey design where a sample of 10 67 students were picked from Jomo Kenyatta University of Agriculture and Technology JKUAT main campus. The findings indicate the use of social networking sites is a viable option as the students are not only members of social networking sites but also that majority have access to the requisite technological devices. Additionally recommendations for ensuring authentic learning were presented. The researcher recommends the exploration of the leveraging of the existing social networking sites for learning in conjunction with key stakeholders.

  3. Structure of Small World Innovation Network and Learning Performance

    Directory of Open Access Journals (Sweden)

    Shuang Song

    2014-01-01

    Full Text Available This paper examines the differences of learning performance of 5 MNCs (multinational corporations that filed the largest number of patents in China. We establish the innovation network with the patent coauthorship data by these 5 MNCs and classify the networks by the tail of distribution curve of connections. To make a comparison of the learning performance of these 5 MNCs with differing network structures, we develop an organization learning model by regarding the reality as having m dimensions, which denotes the heterogeneous knowledge about the reality. We further set n innovative individuals that are mutually interactive and own unique knowledge about the reality. A longer (shorter distance between the knowledge of the individual and the reality denotes a lower (higher knowledge level of that individual. Individuals interact with and learn from each other within the small-world network. By making 1,000 numerical simulations and averaging the simulated results, we find that the differing structure of the small-world network leads to the differences of learning performance between these 5 MNCs. The network monopolization negatively impacts and network connectivity positively impacts learning performance. Policy implications in the conclusion section suggest that to improve firm learning performance, it is necessary to establish a flat and connective network.

  4. First evidence on the validity and reliability of the Safety Organizing Scale-Nursing Home version (SOS-NH).

    Science.gov (United States)

    Ausserhofer, Dietmar; Anderson, Ruth A; Colón-Emeric, Cathleen; Schwendimann, René

    2013-08-01

    The Safety Organizing Scale is a valid and reliable measure on safety behaviors and practices in hospitals. This study aimed to explore the psychometric properties of the Safety Organizing Scale-Nursing Home version (SOS-NH). In a cross-sectional analysis of staff survey data, we examined validity and reliability of the 9-item Safety SOS-NH using American Educational Research Association guidelines. This substudy of a larger trial used baseline survey data collected from staff members (n = 627) in a variety of work roles in 13 nursing homes (NHs) in North Carolina and Virginia. Psychometric evaluation of the SOS-NH revealed good response patterns with low average of missing values across all items (3.05%). Analyses of the SOS-NH's internal structure (eg, comparative fit indices = 0.929, standardized root mean square error of approximation = 0.045) and consistency (composite reliability = 0.94) suggested its 1-dimensionality. Significant between-facility variability, intraclass correlations, within-group agreement, and design effect confirmed appropriateness of the SOS-NH for measurement at the NH level, justifying data aggregation. The SOS-NH showed discriminate validity from one related concept: communication openness. Initial evidence regarding validity and reliability of the SOS-NH supports its utility in measuring safety behaviors and practices among a wide range of NH staff members, including those with low literacy. Further psychometric evaluation should focus on testing concurrent and criterion validity, using resident outcome measures (eg, patient fall rates). Copyright © 2013 American Medical Directors Association, Inc. All rights reserved.

  5. Kinetic and dose dependencies of the SOS-induction in E.coli K-12 (uvrA) cells exposed to different UV doses

    International Nuclear Information System (INIS)

    Komova, O.V.; Kandiano, E.S.; Malavina, G.; )

    2000-01-01

    Kinetic and dose dependencies of the SOS-induction in E. coli (uvrA) cells exposed to UV light were investigated. below 2 J/m 2 the rate of the SOS-induction increased with dose. Maximal level of the SOS-response was proportional to the UV dose. Pyrimidine dimers were necessary for the induction. In the dose range 2-10 J/m 2 the rate of SOS-induction decreased with dose. Dose-maximum response curve was non-linear. Pyrimidine dimers were not required for the induction. nature of the molecular events leading to the SOS-induction at low and high doses was discussed [ru

  6. Chemical trapping and characterization of small oxoacids of sulfur (SOS) generated in aqueous oxidations of H2S.

    Science.gov (United States)

    Kumar, Murugaeson R; Farmer, Patrick J

    2018-04-01

    Small oxoacids of sulfur (SOS) are elusive molecules like sulfenic acid, HSOH, and sulfinic acid, HS(O)OH, generated during the oxidation of hydrogen sulfide, H 2 S, in aqueous solution. Unlike their alkyl homologs, there is a little data on their generation and speciation during H 2 S oxidation. These SOS may exhibit both nucleophilic and electrophilic reactivity, which we attribute to interconversion between S(II) and S(IV) tautomers. We find that SOS may be trapped in situ by derivatization with nucleophilic and electrophilic trapping agents and then characterized by high resolution LC MS. In this report, we compare SOS formation from H 2 S oxidation by a variety of biologically relevant oxidants. These SOS appear relatively long lived in aqueous solution, and thus may be involved in the observed physiological effects of H 2 S. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  7. Evaluation of effects of busulfan and DMA on SOS in pediatric stem cell recipients.

    Science.gov (United States)

    Kerl, Kornelius; Diestelhorst, Christian; Bartelink, Imke; Boelens, Jaap; Trame, Mirjam N; Boos, Joachim; Hempel, Georg

    2014-02-01

    Busulfan (Bu) is a DNA-alkylating agent used for myeloablative conditioning in stem cell transplantation in children and adults. While the use of intravenous rather than oral administration of Bu has reduced inter-individual variability in plasma levels, toxicity still occurs frequently after hematopoietic stem cell transplantation (HSCT). Toxicity (especially hepatotoxic effects) of intravenous (IV) Bu may be related to both Bu and/or N,N-dimethylacetamide (DMA), the solvent of Bu. In this study, we assessed the relation between the exposure of Bu and DMA with regards to the clinical outcome in children from two cohorts. In a two-centre study Bu and DMA AUC (area under the curve) were correlated in pediatric stem cell recipients to the risk of developing SOS and to the clinical outcome. In patients receiving Bu four times per day Bu levels >1,500 µmol/L minute correlate to an increased risk of developing a SOS. In the collective cohort, summarizing data of all 53 patients of this study, neither high area under the curve (AUC) of Bu nor high AUC of DMA appears to be an independent risk factor for the development of SOS in children. In this study neither Bu nor DMA was observed as an independent risk factor for the development of SOS. To identify subgroups (e.g., infants), in which Bu or DMA might be risk factors for the induction of SOS, larger cohorts have to be evaluated. © 2013 Wiley Periodicals, Inc.

  8. Learning and Model-checking Networks of I/O Automata

    DEFF Research Database (Denmark)

    Mao, Hua; Jaeger, Manfred

    2012-01-01

    We introduce a new statistical relational learning (SRL) approach in which models for structured data, especially network data, are constructed as networks of communicating nite probabilistic automata. Leveraging existing automata learning methods from the area of grammatical inference, we can...... learn generic models for network entities in the form of automata templates. As is characteristic for SRL techniques, the abstraction level aorded by learning generic templates enables one to apply the learned model to new domains. A main benet of learning models based on nite automata lies in the fact...

  9. Interconnecting Networks of Practice for Professional Learning

    Directory of Open Access Journals (Sweden)

    Julie Mackey

    2011-03-01

    Full Text Available The article explores the complementary connections between communities of practice and the ways in which individuals orchestrate their engagement with others to further their professional learning. It does so by reporting on part of a research project conducted in New Zealand on teachers’ online professional learning in a university graduate diploma program on ICT education. Evolving from social constructivist pedagogy for online professional development, the research describes how teachers create their own networks of practice as they blend online and offline interactions with fellow learners and workplace colleagues. Teachers’ perspectives of their professional learning activities challenge the way universities design formal online learning communities and highlight the potential for networked learning in the zones and intersections between professional practice and study.The article extends the concepts of Lave and Wenger’s (1991 communities of practice social theory of learning by considering the role participants play in determining their engagement and connections in and across boundaries between online learning communities and professional practice. It provides insights into the applicability of connectivist concepts for developing online pedagogies to promote socially networked learning and for emphasising the role of the learner in defining their learning pathways.

  10. SOS formats and meta-theory : 20 years after

    NARCIS (Netherlands)

    Mousavi, M.R.; Reniers, M.A.; Groote, J.F.

    2007-01-01

    In 1981 Structural Operational Semantics (SOS) was introduced as a systematic way to define operational semantics of programming languages by a set of rules of a certain shape [G.D. Plotkin, A structural approach to operational semantics, Technical Report DAIMI FN-19, Computer Science Department,

  11. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

    Science.gov (United States)

    Firdausiah Mansur, Andi Besse; Yusof, Norazah

    2013-01-01

    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  12. Co-Operative Learning and Development Networks.

    Science.gov (United States)

    Hodgson, V.; McConnell, D.

    1995-01-01

    Discusses the theory, nature, and benefits of cooperative learning. Considers the Cooperative Learning and Development Network (CLDN) trial in the JITOL (Just in Time Open Learning) project and examines the relationship between theories about cooperative learning and the reality of a group of professionals participating in a virtual cooperative…

  13. RpoS plays a central role in the SOS induction by sub-lethal aminoglycoside concentrations in Vibrio cholerae.

    Science.gov (United States)

    Baharoglu, Zeynep; Krin, Evelyne; Mazel, Didier

    2013-01-01

    Bacteria encounter sub-inhibitory concentrations of antibiotics in various niches, where these low doses play a key role for antibiotic resistance selection. However, the physiological effects of these sub-lethal concentrations and their observed connection to the cellular mechanisms generating genetic diversification are still poorly understood. It is known that, unlike for the model bacterium Escherichia coli, sub-minimal inhibitory concentrations (sub-MIC) of aminoglycosides (AGs) induce the SOS response in Vibrio cholerae. SOS is induced upon DNA damage, and since AGs do not directly target DNA, we addressed two issues in this study: how sub-MIC AGs induce SOS in V. cholerae and why they do not do so in E. coli. We found that when bacteria are grown with tobramycin at a concentration 100-fold below the MIC, intracellular reactive oxygen species strongly increase in V. cholerae but not in E. coli. Using flow cytometry and gfp fusions with the SOS regulated promoter of intIA, we followed AG-dependent SOS induction. Testing the different mutation repair pathways, we found that over-expression of the base excision repair (BER) pathway protein MutY relieved this SOS induction in V. cholerae, suggesting a role for oxidized guanine in AG-mediated indirect DNA damage. As a corollary, we established that a BER pathway deficient E. coli strain induces SOS in response to sub-MIC AGs. We finally demonstrate that the RpoS general stress regulator prevents oxidative stress-mediated DNA damage formation in E. coli. We further show that AG-mediated SOS induction is conserved among the distantly related Gram negative pathogens Klebsiella pneumoniae and Photorhabdus luminescens, suggesting that E. coli is more of an exception than a paradigm for the physiological response to antibiotics sub-MIC.

  14. Networks and learning in game theory

    NARCIS (Netherlands)

    Kets, W.

    2008-01-01

    This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network.

  15. Learning as Issue Framing in Agricultural Innovation Networks

    Science.gov (United States)

    Tisenkopfs, Talis; Kunda, Ilona; Šumane, Sandra

    2014-01-01

    Purpose: Networks are increasingly viewed as entities of learning and innovation in agriculture. In this article we explore learning as issue framing in two agricultural innovation networks. Design/methodology/approach: We combine frame analysis and social learning theories to analyse the processes and factors contributing to frame convergence and…

  16. Integral formula for elliptic SOS models with domain walls and a reflecting end

    Energy Technology Data Exchange (ETDEWEB)

    Lamers, Jules, E-mail: j.lamers@uu.nl

    2015-12-15

    In this paper we extend previous work of Galleas and the author to elliptic SOS models. We demonstrate that the dynamical reflection algebra can be exploited to obtain a functional equation characterizing the partition function of an elliptic SOS model with domain-wall boundaries and one reflecting end. Special attention is paid to the structure of the functional equation. Through this approach we find a novel multiple-integral formula for that partition function.

  17. Space Objects Maneuvering Detection and Prediction via Inverse Reinforcement Learning

    Science.gov (United States)

    Linares, R.; Furfaro, R.

    This paper determines the behavior of Space Objects (SOs) using inverse Reinforcement Learning (RL) to estimate the reward function that each SO is using for control. The approach discussed in this work can be used to analyze maneuvering of SOs from observational data. The inverse RL problem is solved using the Feature Matching approach. This approach determines the optimal reward function that a SO is using while maneuvering by assuming that the observed trajectories are optimal with respect to the SO's own reward function. This paper uses estimated orbital elements data to determine the behavior of SOs in a data-driven fashion.

  18. A Decomposition Algorithm for Learning Bayesian Network Structures from Data

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Cordero Hernandez, Jorge

    2008-01-01

    It is a challenging task of learning a large Bayesian network from a small data set. Most conventional structural learning approaches run into the computational as well as the statistical problems. We propose a decomposition algorithm for the structure construction without having to learn...... the complete network. The new learning algorithm firstly finds local components from the data, and then recover the complete network by joining the learned components. We show the empirical performance of the decomposition algorithm in several benchmark networks....

  19. Atomic orbital-based SOS-MP2 with tensor hypercontraction. I. GPU-based tensor construction and exploiting sparsity

    Energy Technology Data Exchange (ETDEWEB)

    Song, Chenchen; Martínez, Todd J. [Department of Chemistry and the PULSE Institute, Stanford University, Stanford, California 94305 (United States); SLAC National Accelerator Laboratory, Menlo Park, California 94025 (United States)

    2016-05-07

    We present a tensor hypercontracted (THC) scaled opposite spin second order Møller-Plesset perturbation theory (SOS-MP2) method. By using THC, we reduce the formal scaling of SOS-MP2 with respect to molecular size from quartic to cubic. We achieve further efficiency by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs) to accelerate integral construction and matrix multiplication. The practical scaling of GPU-accelerated atomic orbital-based THC-SOS-MP2 calculations is found to be N{sup 2.6} for reference data sets of water clusters and alanine polypeptides containing up to 1600 basis functions. The errors in correlation energy with respect to density-fitting-SOS-MP2 are less than 0.5 kcal/mol for all systems tested (up to 162 atoms).

  20. Atomic orbital-based SOS-MP2 with tensor hypercontraction. I. GPU-based tensor construction and exploiting sparsity.

    Science.gov (United States)

    Song, Chenchen; Martínez, Todd J

    2016-05-07

    We present a tensor hypercontracted (THC) scaled opposite spin second order Møller-Plesset perturbation theory (SOS-MP2) method. By using THC, we reduce the formal scaling of SOS-MP2 with respect to molecular size from quartic to cubic. We achieve further efficiency by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs) to accelerate integral construction and matrix multiplication. The practical scaling of GPU-accelerated atomic orbital-based THC-SOS-MP2 calculations is found to be N(2.6) for reference data sets of water clusters and alanine polypeptides containing up to 1600 basis functions. The errors in correlation energy with respect to density-fitting-SOS-MP2 are less than 0.5 kcal/mol for all systems tested (up to 162 atoms).

  1. Learning Bayesian Networks with Incomplete Data by Augmentation

    OpenAIRE

    Adel, Tameem; de Campos, Cassio P.

    2016-01-01

    We present new algorithms for learning Bayesian networks from data with missing values using a data augmentation approach. An exact Bayesian network learning algorithm is obtained by recasting the problem into a standard Bayesian network learning problem without missing data. To the best of our knowledge, this is the first exact algorithm for this problem. As expected, the exact algorithm does not scale to large domains. We build on the exact method to create an approximate algorithm using a ...

  2. THE IMPACTS OF SOCIAL NETWORKING SITES IN HIGHER LEARNING

    OpenAIRE

    Mohd Ishak Bin Ismail; Ruzaini Bin Abdullah Arshah

    2016-01-01

    Social networking sites, a web-based application have permeated the boundary between personal lives and student lives. Nowadays, students in higher learning used social networking site such as Facebook to facilitate their learning through the academic collaboration which it further enhances students’ social capital. Social networking site has many advantages to improve students’ learning. To date, Facebook is the leading social networking sites at this time which it being widely used by stude...

  3. istSOS, a new sensor observation management system: software architecture and a real-case application for flood protection

    Directory of Open Access Journals (Sweden)

    M. Cannata

    2015-11-01

    Full Text Available istSOS (Istituto scienze della Terra Sensor Observation Service is an implementation of the Sensor Observation Service (SOS standard from the Open Geospatial Consortium. The development of istSOS started in 2009 in order to provide a simple implementation of the SOS for the management, provision and integration of hydro-meteorological data collected in Canton Ticino (Southern Switzerland. istSOS is an Open Source, entirely written in Python and based on reliable software like PostgreSQL/PostGIS and Apache/mod_wsgi. This paper illustrates the latest software enhancements, including a RESTful Web service and a Web-based graphical user interface, which enable a better and simplified interaction with measurements and SOS service settings. The robustness of the implemented solution has been validated in a real-case application: the Verbano Lake Early Warning System. In this application, near real-time data have to be exchanged by inter-regional partners and used in a hydrological model for lake level forecasting and flooding hazard assessment. This system is linked with a dedicated geoportal used by the civil protection for the management, alert and protection of the population and the assets of the Locarno area. Practical considerations, technical issues and foreseen improvements are presented and discussed.

  4. Mutation-Specific Mechanisms of Hyperactivation of Noonan Syndrome SOS Molecules Detected with Single-molecule Imaging in Living Cells.

    Science.gov (United States)

    Nakamura, Yuki; Umeki, Nobuhisa; Abe, Mitsuhiro; Sako, Yasushi

    2017-10-26

    Noonan syndrome (NS) is a congenital hereditary disorder associated with developmental and cardiac defects. Some patients with NS carry mutations in SOS, a guanine nucleotide exchange factor (GEF) for the small GTPase RAS. NS mutations have been identified not only in the GEF domain, but also in various domains of SOS, suggesting that multiple mechanisms disrupt SOS function. In this study, we examined three NS mutations in different domains of SOS to clarify the abnormality in its translocation to the plasma membrane, where SOS activates RAS. The association and dissociation kinetics between SOS tagged with a fluorescent protein and the living cell surface were observed in single molecules. All three mutants showed increased affinity for the plasma membrane, inducing excessive RAS signalling. However, the mechanisms by which their affinity was increased were specific to each mutant. Conformational disorder in the resting state, increased probability of a conformational change on the plasma membrane, and an increased association rate constant with the membrane receptor are the suggested mechanisms. These different properties cause the specific phenotypes of the mutants, which should be rescuable with different therapeutic strategies. Therefore, single-molecule kinetic analyses of living cells are useful for the pathological analysis of genetic diseases.

  5. Learning dynamic Bayesian networks with mixed variables

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard

    This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...

  6. Deep learning in neural networks: an overview.

    Science.gov (United States)

    Schmidhuber, Jürgen

    2015-01-01

    In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

  7. Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

    Science.gov (United States)

    Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

    2016-01-01

    Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

  8. DinB Upregulation Is the Sole Role of the SOS Response in Stress-Induced Mutagenesis in Escherichia coli

    Science.gov (United States)

    Galhardo, Rodrigo S.; Do, Robert; Yamada, Masami; Friedberg, Errol C.; Hastings, P. J.; Nohmi, Takehiko; Rosenberg, Susan M.

    2009-01-01

    Stress-induced mutagenesis is a collection of mechanisms observed in bacterial, yeast, and human cells in which adverse conditions provoke mutagenesis, often under the control of stress responses. Control of mutagenesis by stress responses may accelerate evolution specifically when cells are maladapted to their environments, i.e., are stressed. It is therefore important to understand how stress responses increase mutagenesis. In the Escherichia coli Lac assay, stress-induced point mutagenesis requires induction of at least two stress responses: the RpoS-controlled general/starvation stress response and the SOS DNA-damage response, both of which upregulate DinB error-prone DNA polymerase, among other genes required for Lac mutagenesis. We show that upregulation of DinB is the only aspect of the SOS response needed for stress-induced mutagenesis. We constructed two dinB(oc) (operator-constitutive) mutants. Both produce SOS-induced levels of DinB constitutively. We find that both dinB(oc) alleles fully suppress the phenotype of constitutively SOS-“off” lexA(Ind−) mutant cells, restoring normal levels of stress-induced mutagenesis. Thus, dinB is the only SOS gene required at induced levels for stress-induced point mutagenesis. Furthermore, although spontaneous SOS induction has been observed to occur in only a small fraction of cells, upregulation of dinB by the dinB(oc) alleles in all cells does not promote a further increase in mutagenesis, implying that SOS induction of DinB, although necessary, is insufficient to differentiate cells into a hypermutable condition. PMID:19270270

  9. Identifying Gatekeepers in Online Learning Networks

    Science.gov (United States)

    Gursakal, Necmi; Bozkurt, Aras

    2017-01-01

    The rise of the networked society has not only changed our perceptions but also the definitions, roles, processes and dynamics of online learning networks. From offline to online worlds, networks are everywhere and gatekeepers are an important entity in these networks. In this context, the purpose of this paper is to explore gatekeeping and…

  10. Robust Learning of Fixed-Structure Bayesian Networks

    OpenAIRE

    Diakonikolas, Ilias; Kane, Daniel; Stewart, Alistair

    2016-01-01

    We investigate the problem of learning Bayesian networks in an agnostic model where an $\\epsilon$-fraction of the samples are adversarially corrupted. Our agnostic learning model is similar to -- in fact, stronger than -- Huber's contamination model in robust statistics. In this work, we study the fully observable Bernoulli case where the structure of the network is given. Even in this basic setting, previous learning algorithms either run in exponential time or lose dimension-dependent facto...

  11. Motion-insensitive carotid intraplaque hemorrhage imaging using 3D inversion recovery preparation stack of stars (IR-prep SOS) technique.

    Science.gov (United States)

    Kim, Seong-Eun; Roberts, John A; Eisenmenger, Laura B; Aldred, Booth W; Jamil, Osama; Bolster, Bradley D; Bi, Xiaoming; Parker, Dennis L; Treiman, Gerald S; McNally, J Scott

    2017-02-01

    Carotid artery imaging is important in the clinical management of patients at risk for stroke. Carotid intraplaque hemorrhage (IPH) presents an important diagnostic challenge. 3D magnetization prepared rapid acquisition gradient echo (MPRAGE) has been shown to accurately image carotid IPH; however, this sequence can be limited due to motion- and flow-related artifact. The purpose of this work was to develop and evaluate an improved 3D carotid MPRAGE sequence for IPH detection. We hypothesized that a radial-based k-space trajectory sequence such as "Stack of Stars" (SOS) incorporated with inversion recovery preparation would offer reduced motion sensitivity and more robust flow suppression by oversampling of central k-space. A total of 31 patients with carotid disease (62 carotid arteries) were imaged at 3T magnetic resonance imaging (MRI) with 3D IR-prep Cartesian and SOS sequences. Image quality was determined between SOS and Cartesian MPRAGE in 62 carotid arteries using t-tests and multivariable linear regression. Kappa analysis was used to determine interrater reliability. In all, 25 among 62 carotid plaques had carotid IPH by consensus from the reviewers on SOS compared to 24 on Cartesian sequence. Image quality was significantly higher with SOS compared to Cartesian (mean 3.74 vs. 3.11, P SOS acquisition yielded sharper image features with less motion (19.4% vs. 45.2%, P SOS (kappa = 0.89), higher than that of Cartesian (kappa = 0.84). By minimizing flow and motion artifacts and retaining high interrater reliability, the SOS MPRAGE has important advantages over Cartesian MPRAGE in carotid IPH detection. 1 J. Magn. Reson. Imaging 2017;45:410-417. © 2016 International Society for Magnetic Resonance in Medicine.

  12. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

    Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

  13. Design of a Networked Learning Master Environment for Professionals

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    2010-01-01

    The paper is presenting the overall learning design of MIL (Master in ICT and Learning). The learning design is integrating a number of principles: 1. Principles of problem and project based learning 2. Networked learning / learning in communities of practice. The paper will discuss how these pri......The paper is presenting the overall learning design of MIL (Master in ICT and Learning). The learning design is integrating a number of principles: 1. Principles of problem and project based learning 2. Networked learning / learning in communities of practice. The paper will discuss how...

  14. Learning Latent Structure in Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure......Latent structure in complex networks, e.g., in the form of community structure, can help understand network dynamics, identify heterogeneities in network properties, and predict ‘missing’ links. While most community detection algorithms are based on optimizing heuristic clustering objectives...... as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...

  15. Thermodynamic efficiency of learning a rule in neural networks

    Science.gov (United States)

    Goldt, Sebastian; Seifert, Udo

    2017-11-01

    Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.

  16. Mechanism of SOS-induced targeted and untargeted mutagenesis in E. coli

    International Nuclear Information System (INIS)

    Maenhaut-Michel, G.

    1985-01-01

    This paper retraces the evolution of hypotheses concerning mechanisms of SOS induced mutagenesis. Moreover, it reports some recent data which support a new model for the mechanism of targeted and untargeted mutagenesis in E. coli. In summary, the SOS mutator effect, which is responsible for untargeted mutagenesis and perhaps for the misincorporation step in targeted mutagenesis, is believed to involve a fidelity function associated with DNA polymerase III and does not require the umuC gene product. umuC and umuD gene products are probably required specifically for elongation of DNA synthesis past blocking lesions, i.e. to allow mutagenic replication of damaged DNA

  17. Induction of the SOS response in ultraviolet-irradiated Escherichia coli analyzed by dynamics of LexA, RecA and SulA proteins

    International Nuclear Information System (INIS)

    Aksenov, S.V.

    1999-01-01

    The SOS response in Escherichia coli is induced after DNA-damaging treatments including ultraviolet light. Regulation of the SOS response is accomplished through specific interaction of the two SOS regulator proteins, LexA and RecA. In ultraviolet light treated cells nucleotide excision repair is the major system that removes the induced lesions from the DNA. Here, induction of the SOS response in Escherichia coli with normal and impaired excision repair function is studied by simulation of intracellular levels of regulatory LexA and RecA proteins, and SulA protein. SulA protein is responsible for SOS-inducible cell division inhibition. Results of the simulations show that nucleotide excision repair influences time-courses of LexA , RecA and SulA induction by modulating the dynamics of RecA protein distribution between its normal and SOS-activated forms

  18. Kinetic and dose dependences of the SOS-induction in E.coli K-12 (uvrA) cells exposed to the different UV doses

    International Nuclear Information System (INIS)

    Komova, O.V.; Kandiano, E.S.; Malavya, G.

    1999-01-01

    The kinetic and dose dependences of the SOS-induction in E.coli (uvrA) cells exposed to UV light were investigated. Below 2 J/m 2 the rate of the SOS-induction increased with dose. The maximal level of the SOS-response was proportional to the UV dose. Pyrimidine dimers were necessary for the induction. In the dose range 2-10 J/m 2 the rate of the SOS-induction decreased with dose. The dose-response curve was non-linear. Pyrimidine dimers were not required for the induction. The nature of the molecular events leading to the SOS-induction at low and high UV doses was discussed. (author)

  19. Teachers’ motives for learning in networks : costs, rewards and community interest

    NARCIS (Netherlands)

    van den Beemt, A.A.J.; Ketelaar, E.; Diepstraten, I.; de Laat, M.

    2018-01-01

    Background: This paper discusses teachers’ perspectives on learning networks and their motives for participating in these networks. Although it is widely held that teachers’ learning may be developed through learning networks, not all teachers participate in such networks. Purpose: The theme of

  20. Learning Local Components to Understand Large Bayesian Networks

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Xiang, Yanping; Cordero, Jorge

    2009-01-01

    (domain experts) to extract accurate information from a large Bayesian network due to dimensional difficulty. We define a formulation of local components and propose a clustering algorithm to learn such local components given complete data. The algorithm groups together most inter-relevant attributes......Bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. Bayesian learning and reasoning are nontrivial for a large Bayesian network. In parallel, it is a tough job for users...... in a domain. We evaluate its performance on three benchmark Bayesian networks and provide results in support. We further show that the learned components may represent local knowledge more precisely in comparison to the full Bayesian networks when working with a small amount of data....

  1. Evolving autonomous learning in cognitive networks.

    Science.gov (United States)

    Sheneman, Leigh; Hintze, Arend

    2017-12-01

    There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

  2. The SOS Chromotest applied for screening plant antigenotoxic agents against ultraviolet radiation.

    Science.gov (United States)

    Fuentes, J L; García Forero, A; Quintero Ruiz, N; Prada Medina, C A; Rey Castellanos, N; Franco Niño, D A; Contreras García, D A; Córdoba Campo, Y; Stashenko, E E

    2017-09-13

    In this work, we investigated the usefulness of the SOS Chromotest for screening plant antigenotoxic agents against ultraviolet radiation (UV). Fifty Colombian plant extracts obtained by supercritical fluid (CO 2 ) extraction, twelve plant extract constituents (apigenin, carvacrol, β-caryophyllene, 1,8-cineole, citral, p-cymene, geraniol, naringenin, pinocembrin, quercetin, squalene, and thymol) and five standard antioxidant and/or photoprotective agents (curcumin, epigallocatechin gallate, resveratrol, α-tocopherol, and Trolox®) were evaluated for their genotoxicity and antigenotoxicity against UV using the SOS Chromotest. None of the plant extracts, constituents or agents were genotoxic in the SOS Chromotest at tested concentrations. Based on the minimal extract concentration that significantly inhibited UV-genotoxicity (CIG), five plant extracts were antigenotoxic against UV as follows: Baccharis nítida (16 μg mL -1 ) = Solanum crotonifolium (16 μg mL -1 ) > Hyptis suaveolens (31 μg mL -1 ) = Persea caerulea (31 μg mL -1 ) > Lippia origanoides (62 μg mL -1 ). Based on CIG values, the flavonoid compounds showed the highest antigenotoxic potential as follows: apigenin (7 μM) > pinocembrin (15 μM) > quercetin (26 μM) > naringenin (38 μM) > epigallocatechin gallate (108 μM) > resveratrol (642 μM). UV-genotoxicity inhibition with epigallocatechin gallate, naringenin and resveratrol was related to its capability for inhibiting protein synthesis. A correlation analysis between compound antigenotoxicity estimates and antioxidant activity evaluated by the oxygen radical absorbance capacity (ORAC) assay showed that these activities were not related. The usefulness of the SOS Chromotest for bioprospecting of plant antigenotoxic agents against UV was discussed.

  3. Is the S.O.S. diagnostic algorithm applicable to creating highly safe protective systems?

    International Nuclear Information System (INIS)

    Drab, F.

    1994-01-01

    The S.O.S. diagnostic system is analyzed and compared with KOMPARACE and MIN-MAX type diagnostic systems. Designed for the identification of failed sensors, the S.O.S. dynamic algorithm is based on a digital monitoring of output signals from a pair of sensors measuring the same technological parameter. The last 3 output signal data from the two sensors are stored in the algorithm memory. The analysis indicates that S.O.S. is no major achievement in the field of diagnosis because its properties are nearly identical with those of the conventional MIN-MAX system. Some degradation failures of the sensor are incorrectly interpreted by the new algorithm, some failures are not detected at all. From this point of view the new algorithm is inferior to the KOMPARACE type algorithm. (J.B.). 2 figs., 5 refs

  4. Identification of genes involved in low aminoglycoside-induced SOS response in Vibrio cholerae: a role for transcription stalling and Mfd helicase.

    Science.gov (United States)

    Baharoglu, Zeynep; Babosan, Anamaria; Mazel, Didier

    2014-02-01

    Sub-inhibitory concentrations (sub-MIC) of antibiotics play a very important role in selection and development of resistances. Unlike Escherichia coli, Vibrio cholerae induces its SOS response in presence of sub-MIC aminoglycosides. A role for oxidized guanine residues was observed, but the mechanisms of this induction remained unclear. To select for V. cholerae mutants that do not induce low aminoglycoside-mediated SOS induction, we developed a genetic screen that renders induction of SOS lethal. We identified genes involved in this pathway using two strategies, inactivation by transposition and gene overexpression. Interestingly, we obtained mutants inactivated for the expression of proteins known to destabilize the RNA polymerase complex. Reconstruction of the corresponding mutants confirmed their specific involvement in induction of SOS by low aminoglycoside concentrations. We propose that DNA lesions formed on aminoglycoside treatment are repaired through the formation of single-stranded DNA intermediates, inducing SOS. Inactivation of functions that dislodge RNA polymerase leads to prolonged stalling on these lesions, which hampers SOS induction and repair and reduces viability under antibiotic stress. The importance of these mechanisms is illustrated by a reduction of aminoglycoside sub-MIC. Our results point to a central role for transcription blocking at DNA lesions in SOS induction, so far underestimated.

  5. Apoptosis-like death, an extreme SOS response in Escherichia coli.

    Science.gov (United States)

    Erental, Ariel; Kalderon, Ziva; Saada, Ann; Smith, Yoav; Engelberg-Kulka, Hanna

    2014-07-15

    In bacteria, SOS is a global response to DNA damage, mediated by the recA-lexA genes, resulting in cell cycle arrest, DNA repair, and mutagenesis. Previously, we reported that Escherichia coli responds to DNA damage via another recA-lexA-mediated pathway resulting in programmed cell death (PCD). We called it apoptosis-like death (ALD) because it is characterized by membrane depolarization and DNA fragmentation, which are hallmarks of eukaryotic mitochondrial apoptosis. Here, we show that ALD is an extreme SOS response that occurs only under conditions of severe DNA damage. Furthermore, we found that ALD is characterized by additional hallmarks of eukaryotic mitochondrial apoptosis, including (i) rRNA degradation by the endoribonuclease YbeY, (ii) upregulation of a unique set of genes that we called extensive-damage-induced (Edin) genes, (iii) a decrease in the activities of complexes I and II of the electron transport chain, and (iv) the formation of high levels of OH˙ through the Fenton reaction, eventually resulting in cell death. Our genetic and molecular studies on ALD provide additional insight for the evolution of mitochondria and the apoptotic pathway in eukaryotes. Importance: The SOS response is the first described and the most studied bacterial response to DNA damage. It is mediated by a set of two genes, recA-lexA, and it results in DNA repair and thereby in the survival of the bacterial culture. We have shown that Escherichia coli responds to DNA damage by an additional recA-lexA-mediated pathway resulting in an apoptosis-like death (ALD). Apoptosis is a mode of cell death that has previously been reported only in eukaryotes. We found that E. coli ALD is characterized by several hallmarks of eukaryotic mitochondrial apoptosis. Altogether, our results revealed that recA-lexA is a DNA damage response coordinator that permits two opposite responses: life, mediated by the SOS, and death, mediated by the ALD. The choice seems to be a function of the degree

  6. Efficient learning strategy of Chinese characters based on network approach.

    Directory of Open Access Journals (Sweden)

    Xiaoyong Yan

    Full Text Available We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.

  7. Learning Bayesian networks for discrete data

    KAUST Repository

    Liang, Faming; Zhang, Jian

    2009-01-01

    Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly

  8. Refined functional relations for the elliptic SOS model

    Energy Technology Data Exchange (ETDEWEB)

    Galleas, W., E-mail: w.galleas@uu.nl [ARC Centre of Excellence for the Mathematics and Statistics of Complex Systems, University of Melbourne, VIC 3010 (Australia)

    2013-02-21

    In this work we refine the method presented in Galleas (2012) [1] and obtain a novel kind of functional equation determining the partition function of the elliptic SOS model with domain wall boundaries. This functional relation arises from the dynamical Yang-Baxter relation and its solution is given in terms of multiple contour integrals.

  9. Refined functional relations for the elliptic SOS model

    International Nuclear Information System (INIS)

    Galleas, W.

    2013-01-01

    In this work we refine the method presented in Galleas (2012) [1] and obtain a novel kind of functional equation determining the partition function of the elliptic SOS model with domain wall boundaries. This functional relation arises from the dynamical Yang–Baxter relation and its solution is given in terms of multiple contour integrals.

  10. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  11. Multi-modal Social Networks: A MRF Learning Approach

    Science.gov (United States)

    2016-06-20

    Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

  12. Machine Learning Topological Invariants with Neural Networks

    Science.gov (United States)

    Zhang, Pengfei; Shen, Huitao; Zhai, Hui

    2018-02-01

    In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.

  13. Influence of very short patch mismatch repair on SOS inducing lesions after aminoglycoside treatment in Escherichia coli.

    Science.gov (United States)

    Baharoglu, Zeynep; Mazel, Didier

    2014-01-01

    Low concentrations of aminoglycosides induce the SOS response in Vibrio cholerae but not in Escherichia coli. In order to determine whether a specific factor present in E. coli prevents this induction, we developed a genetic screen where only SOS inducing mutants are viable. We identified the vsr gene coding for the Vsr protein of the very short patch mismatch repair (VSPR) pathway. The effect of mismatch repair (MMR) mutants was also studied. We propose that lesions formed upon aminoglycoside treatment are preferentially repaired by VSPR without SOS induction in E. coli and by MMR when VSPR is impaired. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  14. Glutathione S-transferase M1-null genotype as risk factor for SOS in oxaliplatin-treated patients with metastatic colorectal cancer.

    Science.gov (United States)

    Vreuls, C P H; Olde Damink, S W M; Koek, G H; Winstanley, A; Wisse, E; Cloots, R H E; van den Broek, M A J; Dejong, C H C; Bosman, F T; Driessen, A

    2013-02-19

    Oxaliplatin is used as a neo-adjuvant therapy in hepatic colorectal carcinoma metastasis. This treatment has significant side effects, as oxaliplatin is toxic to the sinusoidal endothelial cells and can induce sinusoidal obstruction syndrome (SOS), which is related to decreased overall survival. Glutathione has an important role in the defence system, catalysed by glutathione S-transferase (GST), including two non-enzyme producing polymorphisms (GSTM1-null and GSTT1-null). We hypothesise that patients with a non-enzyme producing polymorphism have a higher risk of developing toxic injury owing to oxaliplatin. In the nontumour-bearing liver, the presence of SOS was studied histopathologically. The genotype was determined by a semi-nested PCR. Thirty-two of the 55 (58%) patients showed SOS lesions, consisting of 27% mild, 22% moderate and 9% severe lesions. The GSTM1-null genotype was present in 25 of the 55 (46%). Multivariate analysis showed that the GSTM1-null genotype significantly correlated with the presence of (moderate-severe) SOS (P=0.026). The GSTM1-null genotype is an independent risk factor for SOS. This finding allows us, in association with other risk factors, to conceive a potential risk profile predicting whether the patient is at risk of developing SOS, before starting oxaliplatin, and subsequently might result in adjustment of treatment.

  15. Functionality for learning networks: lessons learned from social web applications

    NARCIS (Netherlands)

    Berlanga, Adriana; Sloep, Peter; Brouns, Francis; Van Rosmalen, Peter; Bitter-Rijpkema, Marlies; Koper, Rob

    2007-01-01

    Berlanga, A. J., Sloep, P., Brouns, F., Van Rosmalen, P., Bitter-Rijpkema, M., & Koper, R. (2007). Functionality for learning networks: lessons learned from social web applications. Proceedings of the ePortfolio 2007 Conference. October, 18-19, 2007, Maastricht, The Netherlands. [See also

  16. Social networks and performance in distributed learning communities

    OpenAIRE

    Cadima, Rita; Ojeda Rodríguez, Jordi; Monguet Fierro, José María

    2012-01-01

    Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this study we analyse two distributed learning communities' social networks in order to understand how characteristics of the social structure can enhance s...

  17. On-line learning in radial basis functions networks

    OpenAIRE

    Freeman, Jason; Saad, David

    1997-01-01

    An analytic investigation of the average case learning and generalization properties of Radial Basis Function Networks (RBFs) is presented, utilising on-line gradient descent as the learning rule. The analytic method employed allows both the calculation of generalization error and the examination of the internal dynamics of the network. The generalization error and internal dynamics are then used to examine the role of the learning rate and the specialization of the hidden units, which gives ...

  18. Approximation methods for efficient learning of Bayesian networks

    CERN Document Server

    Riggelsen, C

    2008-01-01

    This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order to provide a coherent treatment of matters, thereby helping the reader to gain a thorough understanding of the whole concept of learning Bayesian networks from (in)complete data, this publication combines in a clarifying way all the issues presented in the papers with previously unpublished work.

  19. Adaptive Learning in Weighted Network Games

    NARCIS (Netherlands)

    Bayer, Péter; Herings, P. Jean-Jacques; Peeters, Ronald; Thuijsman, Frank

    2017-01-01

    This paper studies adaptive learning in the class of weighted network games. This class of games includes applications like research and development within interlinked firms, crime within social networks, the economics of pollution, and defense expenditures within allied nations. We show that for

  20. Architecture and performance of radiation-hardened 64-bit SOS/MNOS memory

    International Nuclear Information System (INIS)

    Kliment, D.C.; Ronen, R.S.; Nielsen, R.L.; Seymour, R.N.; Splinter, M.R.

    1976-01-01

    This paper discusses the circuit architecture and performance of a nonvolatile 64-bit MNOS memory fabricated on silicon on sapphire (SOS). The circuit is a test vehicle designed to demonstrate the feasibility of a high-performance, high-density, radiation-hardened MNOS/SOS memory. The array is organized as 16 words by 4 bits and is fully decoded. It utilizes a two-(MNOS) transistor-per-bit cell and differential sensing scheme and is realized in PMOS static resistor load logic. The circuit was fabricated and tested as both a fast write random access memory (RAM) and an electrically alterable read only memory (EAROM) to demonstrate design and process flexibility. Discrete device parameters such as retention, circuit electrical characteristics, and tolerance to total dose and transient radiation are presented

  1. Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

    Science.gov (United States)

    Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

    2017-01-01

    Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

  2. Networks of Learning

    Science.gov (United States)

    Bettencourt, Luis; Kaiser, David

    2004-03-01

    Based on an a historically documented example of scientific discovery - Feynman diagrams as the main calculational tool of theoretical high energy Physics - we map the time evolution of the social network of early adopters through in the US, UK, Japan and the USSR. The spread of the technique for total number of users in each region is then modelled in terms of epidemic models, highlighting parallel and divergent aspects of this analogy. We also show that transient social arrangements develop as the idea is introduced and learned, which later disappear as the technique becomes common knowledge. Such early transient is characterized by abnormally low connectivity distribution powers and by high clustering. This interesting early non-equilibrium stage of network evolution is captured by a new dynamical model for network evolution, which coincides in its long time limit with familiar preferential aggregation dynamics.

  3. Learning Orthographic Structure With Sequential Generative Neural Networks.

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-04-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

  4. Evolution of individual versus social learning on social networks.

    Science.gov (United States)

    Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

    2015-03-06

    A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  5. Biologically-inspired Learning in Pulsed Neural Networks

    DEFF Research Database (Denmark)

    Lehmann, Torsten; Woodburn, Robin

    1999-01-01

    Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the `biologically-inspired' approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks. We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...

  6. Learning oncogenetic networks by reducing to mixed integer linear programming.

    Science.gov (United States)

    Shahrabi Farahani, Hossein; Lagergren, Jens

    2013-01-01

    Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

  7. Mapping Modular SOS to Rewriting Logic

    DEFF Research Database (Denmark)

    Braga, Christiano de Oliveira; Haeusler, Edward Hermann; Meseguer, José

    2003-01-01

    and verification of MSOS specifications, we have defined a mapping, named , from MSOS to rewriting logic (RWL), a logic which has been proposed as a logical and semantic framework. We have proven the correctness of and implemented it as a prototype, the MSOS-SL Interpreter, in the Maude system, a high......Modular SOS (MSOS) is a framework created to improve the modularity of structural operational semantics specifications, a formalism frequently used in the fields of programming languages semantics and process algebras. With the objective of defining formal tools to support the execution...

  8. The Mobile Learning Network: Getting Serious about Games Technologies for Learning

    Science.gov (United States)

    Petley, Rebecca; Parker, Guy; Attewell, Jill

    2011-01-01

    The Mobile Learning Network currently in its third year, is a unique collaborative initiative encouraging and enabling the introduction of mobile learning in English post-14 education. The programme, funded jointly by the Learning and Skills Council and participating colleges and schools and supported by LSN has involved nearly 40,000 learners and…

  9. Learning drifting concepts with neural networks

    NARCIS (Netherlands)

    Biehl, Michael; Schwarze, Holm

    1993-01-01

    The learning of time-dependent concepts with a neural network is studied analytically and numerically. The linearly separable target rule is represented by an N-vector, whose time dependence is modelled by a random or deterministic drift process. A single-layer network is trained online using

  10. Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

    Science.gov (United States)

    Wenhui, Ma; Yu, Wang

    2017-06-01

    Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

  11. Maximum entropy methods for extracting the learned features of deep neural networks.

    Science.gov (United States)

    Finnegan, Alex; Song, Jun S

    2017-10-01

    New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

  12. The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na(+) loading in xylem and confers salt tolerance in transgenic tobacco.

    Science.gov (United States)

    Yadav, Narendra Singh; Shukla, Pushp Sheel; Jha, Anupama; Agarwal, Pradeep K; Jha, Bhavanath

    2012-10-11

    Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1) gene encodes a plasma membrane Na(+)/H(+) antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC), chlorophyll, K(+)/Na(+) ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT) plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS) and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na(+) content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na(+) content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na(+) loading to xylem from root and leaf tissues. Transgenic lines also showed increased K(+) and Ca(2+) content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na(+) efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na(+) content in different organs and also affect the other transporters activity indirectly. These

  13. How to Trigger Emergence and Self-Organisation in Learning Networks

    Science.gov (United States)

    Brouns, Francis; Fetter, Sibren; van Rosmalen, Peter

    The previous chapters of this section discussed why the social structure of Learning Networks is important and present guidelines on how to maintain and allow the emergence of communities in Learning Networks. Chapter 2 explains how Learning Networks rely on social interaction and active participations of the participants. Chapter 3 then continues by presenting guidelines and policies that should be incorporated into Learning Network Services in order to maintain existing communities by creating conditions that promote social interaction and knowledge sharing. Chapter 4 discusses the necessary conditions required for knowledge sharing to occur and to trigger communities to self-organise and emerge. As pointed out in Chap. 4, ad-hoc transient communities facilitate the emergence of social interaction in Learning Networks, self-organising them into communities, taking into account personal characteristics, community characteristics and general guidelines. As explained in Chap. 4 community members would benefit from a service that brings suitable people together for a specific purpose, because it will allow the participant to focus on the knowledge sharing process by reducing the effort or costs. In the current chapter, we describe an example of a peer support Learning Network Service based on the mechanism of peer tutoring in ad-hoc transient communities.

  14. Teachers' Motives for Learning in Networks: Costs, Rewards and Community Interest

    Science.gov (United States)

    van den Beemt, Antoine; Ketelaar, Evelien; Diepstraten, Isabelle; de Laat, Maarten

    2018-01-01

    Background: This paper discusses teachers' perspectives on learning networks and their motives for participating in these networks. Although it is widely held that teachers' learning may be developed through learning networks, not all teachers participate in such networks. Purpose: The theme of reciprocity, central to studies in the area of…

  15. Lex marks the spot: the virulent side of SOS and a closer look at the LexA regulon.

    Science.gov (United States)

    Kelley, William L

    2006-12-01

    The SOS response that responds to DNA damage induces many genes that are under LexA repression. A detailed examination of LexA regulons using genome-wide techniques has recently been undertaken in both Escherichia coli and Bacillus subtilis. These extensive and elegant studies have now charted the extent of the LexA regulons, uncovered many new genes, and exposed a limited overlap in the LexA regulon between the two bacteria. As more bacterial genomes are analysed, more curiosities in LexA regulons arise. Several notable examples include the discovery of a LexA-like protein, HdiR, in Lactococcus lactis, organisms with two lexA genes, and small DNA damage-inducible cassettes under LexA control. In the cyanobacterium Synechocystis, genetic and microarray studies demonstrated that a LexA paralogue exerts control over an entirely different set of carbon-controlled genes and is crucial to cells facing carbon starvation. An examination of SOS induction evoked by common therapeutic drugs has shed new light on unsuspected consequences of drug exposure. Certain antibiotics, most notably fluoroquinolones such as ciprofloxacin, can induce an SOS response and can modulate the spread of virulence factors and drug resistance. SOS induction by beta-lactams in E. coli triggers a novel form of antibiotic defence that involves cell wall stress and signal transduction by the DpiAB two-component system. In this review, we provide an overview of these new directions in SOS and LexA research with emphasis on a few themes: identification of genes under LexA control, the identification of new endogenous triggers, and antibiotic-induced SOS response and its consequences.

  16. NKS1, Na+- and K+-sensitive 1, regulates ion homeostasis in an SOS-independent pathway in Arabidopsis

    KAUST Repository

    Choi, Wonkyun

    2011-04-01

    An Arabidopsis thaliana mutant, nks1-1, exhibiting enhanced sensitivity to NaCl was identified in a screen of a T-DNA insertion population in the genetic background of Col-0 gl1 sos3-1. Analysis of the genome sequence in the region flanking the T-DNA left border indicated two closely linked mutations in the gene encoded at locus At4g30996. A second allele, nks1-2, was obtained from the Arabidopsis Biological Resource Center. NKS1 mRNA was detected in all parts of wild-type plants but was not detected in plants of either mutant, indicating inactivation by the mutations. Both mutations in NKS1 were associated with increased sensitivity to NaCl and KCl, but not to LiCl or mannitol. NaCl sensitivity was associated with nks1 mutations in Arabidopsis lines expressing either wild type or alleles of SOS1, SOS2 or SOS3. The NaCl-sensitive phenotype of the nks1-2 mutant was complemented by expression of a full-length NKS1 allele from the CaMV35S promoter. When grown in medium containing NaCl, nks1 mutants accumulated more Na+ than wild type and K +/Na+ homeostasis was perturbed. It is proposed NKS1, a plant-specific gene encoding a 19 kDa endomembrane-localized protein of unknown function, is part of an ion homeostasis regulation pathway that is independent of the SOS pathway. © 2011 Elsevier Ltd. All rights reserved.

  17. NKS1, Na+- and K+-sensitive 1, regulates ion homeostasis in an SOS-independent pathway in Arabidopsis

    KAUST Repository

    Choi, Wonkyun; Baek, Dongwon; Oh, Dongha; Park, Jiyoung; Hong, Hyewon; Kim, Woeyeon; Bohnert, Hans Jü rgen; Bressan, Ray Anthony; Park, Hyeongcheol; Yun, Daejin

    2011-01-01

    An Arabidopsis thaliana mutant, nks1-1, exhibiting enhanced sensitivity to NaCl was identified in a screen of a T-DNA insertion population in the genetic background of Col-0 gl1 sos3-1. Analysis of the genome sequence in the region flanking the T-DNA left border indicated two closely linked mutations in the gene encoded at locus At4g30996. A second allele, nks1-2, was obtained from the Arabidopsis Biological Resource Center. NKS1 mRNA was detected in all parts of wild-type plants but was not detected in plants of either mutant, indicating inactivation by the mutations. Both mutations in NKS1 were associated with increased sensitivity to NaCl and KCl, but not to LiCl or mannitol. NaCl sensitivity was associated with nks1 mutations in Arabidopsis lines expressing either wild type or alleles of SOS1, SOS2 or SOS3. The NaCl-sensitive phenotype of the nks1-2 mutant was complemented by expression of a full-length NKS1 allele from the CaMV35S promoter. When grown in medium containing NaCl, nks1 mutants accumulated more Na+ than wild type and K +/Na+ homeostasis was perturbed. It is proposed NKS1, a plant-specific gene encoding a 19 kDa endomembrane-localized protein of unknown function, is part of an ion homeostasis regulation pathway that is independent of the SOS pathway. © 2011 Elsevier Ltd. All rights reserved.

  18. Novel Escherichia coli umuD′ Mutants: Structure-Function Insights into SOS Mutagenesis

    Science.gov (United States)

    McLenigan, Mary; Peat, Thomas S.; Frank, Ekaterina G.; McDonald, John P.; Gonzalez, Martín; Levine, Arthur S.; Hendrickson, Wayne A.; Woodgate, Roger

    1998-01-01

    Although it has been 10 years since the discovery that the Escherichia coli UmuD protein undergoes a RecA-mediated cleavage reaction to generate mutagenically active UmuD′, the function of UmuD′ has yet to be determined. In an attempt to elucidate the role of UmuD′ in SOS mutagenesis, we have utilized a colorimetric papillation assay to screen for mutants of a hydroxylamine-treated, low-copy-number umuD′ plasmid that are unable to promote SOS-dependent spontaneous mutagenesis. Using such an approach, we have identified 14 independent umuD′ mutants. Analysis of these mutants revealed that two resulted from promoter changes which reduced the expression of wild-type UmuD′, three were nonsense mutations that resulted in a truncated UmuD′ protein, and the remaining nine were missense alterations. In addition to the hydroxylamine-generated mutants, we have subcloned the mutations found in three chromosomal umuD1, umuD44, and umuD77 alleles into umuD′. All 17 umuD′ mutants resulted in lower levels of SOS-dependent spontaneous mutagenesis but varied in the extent to which they promoted methyl methanesulfonate-induced mutagenesis. We have attempted to correlate these phenotypes with the potential effect of each mutation on the recently described structure of UmuD′. PMID:9721309

  19. Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

    Directory of Open Access Journals (Sweden)

    Wenhui Ma

    2017-06-01

    Full Text Available Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

  20. Starvation, Together with the SOS Response, Mediates High Biofilm-Specific Tolerance to the Fluoroquinolone Ofloxacin

    Science.gov (United States)

    Bernier, Steve P.; Lebeaux, David; DeFrancesco, Alicia S.; Valomon, Amandine; Soubigou, Guillaume; Coppée, Jean-Yves; Ghigo, Jean-Marc; Beloin, Christophe

    2013-01-01

    High levels of antibiotic tolerance are a hallmark of bacterial biofilms. In contrast to well-characterized inherited antibiotic resistance, molecular mechanisms leading to reversible and transient antibiotic tolerance displayed by biofilm bacteria are still poorly understood. The physiological heterogeneity of biofilms influences the formation of transient specialized subpopulations that may be more tolerant to antibiotics. In this study, we used random transposon mutagenesis to identify biofilm-specific tolerant mutants normally exhibited by subpopulations located in specialized niches of heterogeneous biofilms. Using Escherichia coli as a model organism, we demonstrated, through identification of amino acid auxotroph mutants, that starved biofilms exhibited significantly greater tolerance towards fluoroquinolone ofloxacin than their planktonic counterparts. We demonstrated that the biofilm-associated tolerance to ofloxacin was fully dependent on a functional SOS response upon starvation to both amino acids and carbon source and partially dependent on the stringent response upon leucine starvation. However, the biofilm-specific ofloxacin increased tolerance did not involve any of the SOS-induced toxin–antitoxin systems previously associated with formation of highly tolerant persisters. We further demonstrated that ofloxacin tolerance was induced as a function of biofilm age, which was dependent on the SOS response. Our results therefore show that the SOS stress response induced in heterogeneous and nutrient-deprived biofilm microenvironments is a molecular mechanism leading to biofilm-specific high tolerance to the fluoroquinolone ofloxacin. PMID:23300476

  1. Social networks as ICT collaborative and supportive learning media ...

    African Journals Online (AJOL)

    ... ICT collaborative and supportive learning media utilisation within the Nigerian educational system. The concept of ICT was concisely explained vis-à-vis the social network concept, theory and collaborative and supportive learning media utilisation. Different types of social network are highlighted among which Facebook, ...

  2. Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

    Science.gov (United States)

    van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

    2016-01-01

    E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…

  3. Exploring Practice-Research Networks for Critical Professional Learning

    Science.gov (United States)

    Appleby, Yvon; Hillier, Yvonne

    2012-01-01

    This paper discusses the contribution that practice-research networks can make to support critical professional development in the Learning and Skills sector in England. By practice-research networks we mean groups or networks which maintain a connection between research and professional practice. These networks stem from the philosophy of…

  4. Regulation of the E. coli SOS response by the lexA gene product

    International Nuclear Information System (INIS)

    Brent, R.

    1983-01-01

    In an Escherichia coli that is growing normally, transcription of many genes is repressed by the product of the lexA gene. If cellular DNA is damaged, proteolytically competent recA protein (recA protease) inactivates lexA protein and these genes are induced. Many of the cellular phenomena observed during the cellular response to DNA damage (the SOS response) are the consequence of the expression of these lexA-prepressed genes. Since the SOS response of E. coli has recently been the subject of a comprehensive review, in this paper I would like to concentrate on some modifications to the picture based on new data. 12 references, 2 figures

  5. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa

    The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....

  6. Logarithmic learning for generalized classifier neural network.

    Science.gov (United States)

    Ozyildirim, Buse Melis; Avci, Mutlu

    2014-12-01

    Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Towards a Social Networks Model for Online Learning & Performance

    Science.gov (United States)

    Chung, Kon Shing Kenneth; Paredes, Walter Christian

    2015-01-01

    In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…

  8. Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

    Science.gov (United States)

    Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

    2017-08-01

    This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

  9. DNA compaction in the early part of the SOS response is dependent on RecN and RecA.

    Science.gov (United States)

    Odsbu, Ingvild; Skarstad, Kirsten

    2014-05-01

    The nucleoids of undamaged Escherichia coli cells have a characteristic shape and number, which is dependent on the growth medium. Upon induction of the SOS response by a low dose of UV irradiation an extensive reorganization of the nucleoids occurred. Two distinct phases were observed by fluorescence microscopy. First, the nucleoids were found to change shape and fuse into compact structures at midcell. The compaction of the nucleoids lasted for 10-20 min and was followed by a phase where the DNA was dispersed throughout the cells. This second phase lasted for ~1 h. The compaction was found to be dependent on the recombination proteins RecA, RecO and RecR as well as the SOS-inducible, SMC (structural maintenance of chromosomes)-like protein RecN. RecN protein is produced in high amounts during the first part of the SOS response. It is possible that the RecN-mediated 'compact DNA' stage at the beginning of the SOS response serves to stabilize damaged DNA prior to recombination and repair.

  10. The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na+ loading in xylem and confers salt tolerance in transgenic tobacco

    Directory of Open Access Journals (Sweden)

    Yadav Narendra

    2012-10-01

    Full Text Available Abstract Background Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1 gene encodes a plasma membrane Na+/H+ antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. Results The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC, chlorophyll, K+/Na+ ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na+ content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na+ content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na+ loading to xylem from root and leaf tissues. Transgenic lines also showed increased K+ and Ca2+ content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. Conclusions Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na+ efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na+ content in different organs and also affect the other

  11. The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na+ loading in xylem and confers salt tolerance in transgenic tobacco

    Science.gov (United States)

    2012-01-01

    Background Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1) gene encodes a plasma membrane Na+/H+ antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. Results The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC), chlorophyll, K+/Na+ ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT) plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS) and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na+ content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na+ content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na+ loading to xylem from root and leaf tissues. Transgenic lines also showed increased K+ and Ca2+ content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. Conclusions Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na+ efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na+ content in different organs and also affect the other transporters activity indirectly

  12. Networked Learning and Network Science: Potential Applications to Health Professionals' Continuing Education and Development.

    Science.gov (United States)

    Margolis, Alvaro; Parboosingh, John

    2015-01-01

    Prior interpersonal relationships and interactivity among members of professional associations may impact the learning process in continuing medical education (CME). On the other hand, CME programs that encourage interactivity between participants may impact structures and behaviors in these professional associations. With the advent of information and communication technologies, new communication spaces have emerged that have the potential to enhance networked learning in national and international professional associations and increase the effectiveness of CME for health professionals. In this article, network science, based on the application of network theory and other theories, is proposed as an approach to better understand the contribution networking and interactivity between health professionals in professional communities make to their learning and adoption of new practices over time. © 2015 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.

  13. Network anomaly detection a machine learning perspective

    CERN Document Server

    Bhattacharyya, Dhruba Kumar

    2013-01-01

    With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents mach

  14. SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

    Science.gov (United States)

    Zenke, Friedemann; Ganguli, Surya

    2018-04-13

    A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

  15. Social Networking Sites and Language Learning

    Science.gov (United States)

    Brick, Billy

    2011-01-01

    This article examines a study of seven learners who logged their experiences on the language leaning social networking site Livemocha over a period of three months. The features of the site are described and the likelihood of their future success is considered. The learners were introduced to the Social Networking Site (SNS) and asked to learn a…

  16. Proceedings of the NKS/SOS-2 seminar on risk informed principles

    International Nuclear Information System (INIS)

    Pulkkinen, U.; Simola, K.

    1999-09-01

    The aim of this NKS/SOS-2 seminar was to present the status and plans of applications of Risk Informed Principles both by nuclear authorities and industry in Finland and Sweden. Furthermore, views from the off-shore industry were presented. (EHS)

  17. Learning and forgetting on asymmetric, diluted neural networks

    International Nuclear Information System (INIS)

    Derrida, B.; Nadal, J.P.

    1987-01-01

    It is possible to construct diluted asymmetric models of neural networks for which the dynamics can be calculated exactly. The authors test several learning schemes, in particular, models for which the values of the synapses remain bounded and depend on the history. Our analytical results on the relative efficiencies of the various learning schemes are qualitatively similar to the corresponding ones obtained numerically on fully connected symmetric networks

  18. Learning Networks: connecting people, organizations, autonomous agents and learning resources to establish the emergence of effective lifelong learning

    NARCIS (Netherlands)

    Koper, Rob; Sloep, Peter

    2003-01-01

    Koper, E.J.R., Sloep, P.B. (2002) Learning Networks connecting people, organizations, autonomous agents and learning resources to establish the emergence of effective lifelong learning. RTD Programma into Learning Technologies 2003-2008. More is different… Heerlen, Nederland: Open Universiteit

  19. Disseminating Innovations in Teaching Value-Based Care Through an Online Learning Network.

    Science.gov (United States)

    Gupta, Reshma; Shah, Neel T; Moriates, Christopher; Wallingford, September; Arora, Vineet M

    2017-08-01

    A national imperative to provide value-based care requires new strategies to teach clinicians about high-value care. We developed a virtual online learning network aimed at disseminating emerging strategies in teaching value-based care. The online Teaching Value in Health Care Learning Network includes monthly webinars that feature selected innovators, online discussion forums, and a repository for sharing tools. The learning network comprises clinician-educators and health system leaders across North America. We conducted a cross-sectional online survey of all webinar presenters and the active members of the network, and we assessed program feasibility. Six months after the program launched, there were 277 learning community members in 22 US states. Of the 74 active members, 50 (68%) completed the evaluation. Active members represented independently practicing physicians and trainees in 7 specialties, nurses, educators, and health system leaders. Nearly all speakers reported that the learning network provided them with a unique opportunity to connect with a different audience and achieve greater recognition for their work. Of the members who were active in the learning network, most reported that strategies gleaned from the network were helpful, and some adopted or adapted these innovations at their home institutions. One year after the program launched, the learning network had grown to 364 total members. The learning network helped participants share and implement innovations to promote high-value care. The model can help disseminate innovations in emerging areas of health care transformation, and is sustainable without ongoing support after a period of start-up funding.

  20. A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks

    NARCIS (Netherlands)

    De Jong, Tim; Fuertes, Alba; Schmeits, Tally; Specht, Marcus; Koper, Rob

    2008-01-01

    De Jong, T., Fuertes, A., Schmeits, T., Specht, M., & Koper, R. (2009). A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks. In D. Goh (Ed.), Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education (pp.

  1. The SOS-LUX-LAC-FLUORO-Toxicity-test on the International Space Station (ISS).

    Science.gov (United States)

    Rabbow, E; Rettberg, P; Baumstark-Khan, C; Horneck, G

    2003-01-01

    In the 21st century, an increasing number of astronauts will visit the International Space Station (ISS) for prolonged times. Therefore it is of utmost importance to provide necessary basic knowledge concerning risks to their health and their ability to work on the station and during extravehicular activities (EVA) in free space. It is the aim of one experiment of the German project TRIPLE-LUX (to be flown on the ISS) to provide an estimation of health risk resulting from exposure of the astronauts to the radiation in space inside the station as well as during extravehicular activities on one hand, and of exposure of astronauts to unavoidable or as yet unknown ISS-environmental genotoxic substances on the other. The project will (i) provide increased knowledge of the biological action of space radiation and enzymatic repair of DNA damage, (ii) uncover cellular mechanisms of synergistic interaction of microgravity and space radiation and (iii) examine the space craft milieu with highly specific biosensors. For these investigations, the bacterial biosensor SOS-LUX-LAC-FLUORO-Toxicity-test will be used, combining the SOS-LUX-Test invented at DLR Germany (Patent) with the commercially available LAC-FLUORO-Test. The SOS-LUX-Test comprises genetically modified bacteria transformed with the pBR322-derived plasmid pPLS-1. This plasmid carries the promoterless lux operon of Photobacterium leiognathi as a reporter element under control of the DNA-damage dependent SOS promoter of ColD as sensor element. This system reacts to radiation and other agents that induce DNA damages with a dose dependent measurable emission of bioluminescence of the transformed bacteria. The analogous LAC-FLUORO-Test has been developed for the detection of cellular responses to cytotoxins. It is based on the constitutive expression of green fluorescent protein (GFP) mediated by the bacterial protein expression vector pGFPuv (Clontech, Palo Alto, USA). In response to cytotoxic agents, this system

  2. Activation of Extracellular Signal-Regulated Kinase but Not of p38 Mitogen-Activated Protein Kinase Pathways in Lymphocytes Requires Allosteric Activation of SOS

    Science.gov (United States)

    Jun, Jesse E.; Yang, Ming; Chen, Hang; Chakraborty, Arup K.

    2013-01-01

    Thymocytes convert graded T cell receptor (TCR) signals into positive selection or deletion, and activation of extracellular signal-related kinase (ERK), p38, and Jun N-terminal protein kinase (JNK) mitogen-activated protein kinases (MAPKs) has been postulated to play a discriminatory role. Two families of Ras guanine nucleotide exchange factors (RasGEFs), SOS and RasGRP, activate Ras and the downstream RAF-MEK-ERK pathway. The pathways leading to lymphocyte p38 and JNK activation are less well defined. We previously described how RasGRP alone induces analog Ras-ERK activation while SOS and RasGRP cooperate to establish bimodal ERK activation. Here we employed computational modeling and biochemical experiments with model cell lines and thymocytes to show that TCR-induced ERK activation grows exponentially in thymocytes and that a W729E allosteric pocket mutant, SOS1, can only reconstitute analog ERK signaling. In agreement with RasGRP allosterically priming SOS, exponential ERK activation is severely decreased by pharmacological or genetic perturbation of the phospholipase Cγ (PLCγ)-diacylglycerol-RasGRP1 pathway. In contrast, p38 activation is not sharply thresholded and requires high-level TCR signal input. Rac and p38 activation depends on SOS1 expression but not allosteric activation. Based on computational predictions and experiments exploring whether SOS functions as a RacGEF or adaptor in Rac-p38 activation, we established that the presence of SOS1, but not its enzymatic activity, is critical for p38 activation. PMID:23589333

  3. Stochastic sensitivity analysis and Langevin simulation for neural network learning

    International Nuclear Information System (INIS)

    Koda, Masato

    1997-01-01

    A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method

  4. Physics Teacher SOS: Supporting New Teachers without Pushing an Agenda

    Science.gov (United States)

    Baird, Dean

    2013-01-01

    Few workshops for teachers focus primarily on instruction methods for basic high school physics. In Northern California, Physics Teacher SOS (PTSOS) has gained popularity doing just that. PTSOS workshops are directed toward early-career science teachers, though veterans are welcome too. The program is not influenced by scientific supply companies,…

  5. Reinforcement learning account of network reciprocity.

    Science.gov (United States)

    Ezaki, Takahiro; Masuda, Naoki

    2017-01-01

    Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model) approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node's degree. Thus, we significantly extend previously obtained numerical results.

  6. Boltzmann learning of parameters in cellular neural networks

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    1992-01-01

    The use of Bayesian methods to design cellular neural networks for signal processing tasks and the Boltzmann machine learning rule for parameter estimation is discussed. The learning rule can be used for models with hidden units, or for completely unsupervised learning. The latter is exemplified...

  7. Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

    Science.gov (United States)

    López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2015-04-15

    Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. A Probability-based Evolutionary Algorithm with Mutations to Learn Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Sho Fukuda

    2014-12-01

    Full Text Available Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that several studies have been tried to achieve. In recent years, probability-based evolutionary algorithms have been proposed as a new efficient approach to learn Bayesian networks. In this paper, we target on one of the probability-based evolutionary algorithms called PBIL (Probability-Based Incremental Learning, and propose a new mutation operator. Through performance evaluation, we found that the proposed mutation operator has a good performance in learning Bayesian networks

  9. Collaborative Supervised Learning for Sensor Networks

    Science.gov (United States)

    Wagstaff, Kiri L.; Rebbapragada, Umaa; Lane, Terran

    2011-01-01

    Collaboration methods for distributed machine-learning algorithms involve the specification of communication protocols for the learners, which can query other learners and/or broadcast their findings preemptively. Each learner incorporates information from its neighbors into its own training set, and they are thereby able to bootstrap each other to higher performance. Each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. After being seeded with an initial labeled training set, each learner proceeds to learn in an iterative fashion. New data is collected and classified. The learner can then either broadcast its most confident classifications for use by other learners, or can query neighbors for their classifications of its least confident items. As such, collaborative learning combines elements of both passive (broadcast) and active (query) learning. It also uses ideas from ensemble learning to combine the multiple responses to a given query into a single useful label. This approach has been evaluated against current non-collaborative alternatives, including training a single classifier and deploying it at all nodes with no further learning possible, and permitting learners to learn from their own most confident judgments, absent interaction with their neighbors. On several data sets, it has been consistently found that active collaboration is the best strategy for a distributed learner network. The main advantages include the ability for learning to take place autonomously by collaboration rather than by requiring intervention from an oracle (usually human), and also the ability to learn in a distributed environment, permitting decisions to be made in situ and to yield faster response time.

  10. Radiation-hardened CMOS/SOS LSI circuits

    International Nuclear Information System (INIS)

    Aubuchon, K.G.; Peterson, H.T.; Shumake, D.P.

    1976-01-01

    The recently developed technology for building radiation-hardened CMOS/SOS devices has now been applied to the fabrication of LSI circuits. This paper describes and presents results on three different circuits: an 8-bit adder/subtractor (Al gate), a 256-bit shift register (Si gate), and a polycode generator (Al gate). The 256-bit shift register shows very little degradation after 1 x 10 6 rads (Si), with an increase from 1.9V to 2.9V in minimum operating voltage, a decrease of about 20% in maximum frequency, and little or no change in quiescent current. The p-channel thresholds increase from -0.9V to -1.3V, while the n-channel thresholds decrease from 1.05 to 0.23V, and the n-channel leakage remains below 1nA/mil. Excellent hardening results were also obtained on the polycode generator circuit. Ten circuits were irradiated to 1 x 10 6 rads (Si), and all continued to function well, with an increase in minimum power supply voltage from 2.85V to 5.85V and an increase in quiescent current by a factor of about 2. Similar hardening results were obtained on the 8-bit adder, with the minimum power supply voltage increasing from 2.2V to 4.6V and the add time increasing from 270 to 350 nsec after 1 x 10 6 rads (Si). These results show that large CMOS/SOS circuits can be hardened to above 1 x 10 6 rads (Si) with either the Si gate or Al gate technology. The paper also discusses the relative advantages of the Si gate versus the Al gate technology

  11. Learning Errors by Radial Basis Function Neural Networks and Regularization Networks

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman; Vidnerová, Petra

    2009-01-01

    Roč. 1, č. 2 (2009), s. 49-57 ISSN 2005-4262 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : neural network * RBF networks * regularization * learning Subject RIV: IN - Informatics, Computer Science http://www.sersc.org/journals/IJGDC/vol2_no1/5.pdf

  12. Learning State Space Dynamics in Recurrent Networks

    Science.gov (United States)

    Simard, Patrice Yvon

    Fully recurrent (asymmetrical) networks can be used to learn temporal trajectories. The network is unfolded in time, and backpropagation is used to train the weights. The presence of recurrent connections creates internal states in the system which vary as a function of time. The resulting dynamics can provide interesting additional computing power but learning is made more difficult by the existence of internal memories. This study first exhibits the properties of recurrent networks in terms of convergence when the internal states of the system are unknown. A new energy functional is provided to change the weights of the units in order to the control the stability of the fixed points of the network's dynamics. The power of the resultant algorithm is illustrated with the simulation of a content addressable memory. Next, the more general case of time trajectories on a recurrent network is studied. An application is proposed in which trajectories are generated to draw letters as a function of an input. In another application of recurrent systems, a neural network certain temporal properties observed in human callosally sectioned brains. Finally the proposed algorithm for stabilizing dynamics around fixed points is extended to one for stabilizing dynamics around time trajectories. Its effects are illustrated on a network which generates Lisajous curves.

  13. Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

    Science.gov (United States)

    Kulkarni, Shruti R; Rajendran, Bipin

    2018-07-01

    We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse biological spike rates below 300Hz achieves a classification accuracy of 98.17% on the MNIST test database with four times fewer parameters compared to the state-of-the-art. We present several insights from extensive numerical experiments regarding optimization of learning parameters and network configuration to improve its accuracy. We also describe a number of strategies to optimize the SNN for implementation in memory and energy constrained hardware, including approximations in computing the neuronal dynamics and reduced precision in storing the synaptic weights. Experiments reveal that even with 3-bit synaptic weights, the classification accuracy of the designed SNN does not degrade beyond 1% as compared to the floating-point baseline. Further, the proposed SNN, which is trained based on the precise spike timing information outperforms an equivalent non-spiking artificial neural network (ANN) trained using back propagation, especially at low bit precision. Thus, our study shows the potential for realizing efficient neuromorphic systems that use spike based information encoding and learning for real-world applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Problems in the Deployment of Learning Networks In Small Organizations

    NARCIS (Netherlands)

    Shankle, Dean E.; Shankle, Jeremy P.

    2006-01-01

    Please, cite this publication as: Shankle, D.E., & Shankle, J.P. (2006). Problems in the Deployment of Learning Networks In Small Organizations. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia, Bulgaria:

  15. Specificity determinants for autoproteolysis of LexA, a key regulator of bacterial SOS mutagenesis.

    Science.gov (United States)

    Mo, Charlie Y; Birdwell, L Dillon; Kohli, Rahul M

    2014-05-20

    Bacteria utilize the tightly regulated stress response (SOS) pathway to respond to a variety of genotoxic agents, including antimicrobials. Activation of the SOS response is regulated by a key repressor-protease, LexA, which undergoes autoproteolysis in the setting of stress, resulting in derepression of SOS genes. Remarkably, genetic inactivation of LexA's self-cleavage activity significantly decreases acquired antibiotic resistance in infection models and renders bacteria hypersensitive to traditional antibiotics, suggesting that a mechanistic study of LexA could help inform its viability as a novel target for combating acquired drug resistance. Despite structural insights into LexA, a detailed knowledge of the enzyme's protease specificity is lacking. Here, we employ saturation and positional scanning mutagenesis on LexA's internal cleavage region to analyze >140 mutants and generate a comprehensive specificity profile of LexA from the human pathogen Pseudomonas aeruginosa (LexAPa). We find that the LexAPa active site possesses a unique mode of substrate recognition. Positions P1-P3 prefer small hydrophobic residues that suggest specific contacts with the active site, while positions P5 and P1' show a preference for flexible glycine residues that may facilitate the conformational change that permits autoproteolysis. We further show that stabilizing the β-turn within the cleavage region enhances LexA autoproteolytic activity. Finally, we identify permissive positions flanking the scissile bond (P4 and P2') that are tolerant to extensive mutagenesis. Our studies shed light on the active site architecture of the LexA autoprotease and provide insights that may inform the design of probes of the SOS pathway.

  16. A Self-Organizing Incremental Neural Network based on local distribution learning.

    Science.gov (United States)

    Xing, Youlu; Shi, Xiaofeng; Shen, Furao; Zhou, Ke; Zhao, Jinxi

    2016-12-01

    In this paper, we propose an unsupervised incremental learning neural network based on local distribution learning, which is called Local Distribution Self-Organizing Incremental Neural Network (LD-SOINN). The LD-SOINN combines the advantages of incremental learning and matrix learning. It can automatically discover suitable nodes to fit the learning data in an incremental way without a priori knowledge such as the structure of the network. The nodes of the network store rich local information regarding the learning data. The adaptive vigilance parameter guarantees that LD-SOINN is able to add new nodes for new knowledge automatically and the number of nodes will not grow unlimitedly. While the learning process continues, nodes that are close to each other and have similar principal components are merged to obtain a concise local representation, which we call a relaxation data representation. A denoising process based on density is designed to reduce the influence of noise. Experiments show that the LD-SOINN performs well on both artificial and real-word data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Parameter diagnostics of phases and phase transition learning by neural networks

    Science.gov (United States)

    Suchsland, Philippe; Wessel, Stefan

    2018-05-01

    We present an analysis of neural network-based machine learning schemes for phases and phase transitions in theoretical condensed matter research, focusing on neural networks with a single hidden layer. Such shallow neural networks were previously found to be efficient in classifying phases and locating phase transitions of various basic model systems. In order to rationalize the emergence of the classification process and for identifying any underlying physical quantities, it is feasible to examine the weight matrices and the convolutional filter kernels that result from the learning process of such shallow networks. Furthermore, we demonstrate how the learning-by-confusing scheme can be used, in combination with a simple threshold-value classification method, to diagnose the learning parameters of neural networks. In particular, we study the classification process of both fully-connected and convolutional neural networks for the two-dimensional Ising model with extended domain wall configurations included in the low-temperature regime. Moreover, we consider the two-dimensional XY model and contrast the performance of the learning-by-confusing scheme and convolutional neural networks trained on bare spin configurations to the case of preprocessed samples with respect to vortex configurations. We discuss these findings in relation to similar recent investigations and possible further applications.

  18. Regulated expression of the dinR and recA genes during competence development and SOS induction in Bacillus subtilis

    NARCIS (Netherlands)

    Haijema, BJ; vanSinderen, D; Winterling, K; Kooistra, J; Venema, G; Hamoen, LW

    1996-01-01

    It has been hypothesized that the dinR gene product of Bacillus subtilis acts as a repressor of the SOS regulon by binding to DNA sequences located upstream of SOS genes, including dinR and recA. Following activation as a result of DNA damage, RecA is believed to catalyse DinR-autocleavage, thus

  19. Reinforcement learning account of network reciprocity.

    Directory of Open Access Journals (Sweden)

    Takahiro Ezaki

    Full Text Available Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node's degree. Thus, we significantly extend previously obtained numerical results.

  20. Activation of multiple signaling pathways causes developmental defects in mice with a Noonan syndrome–associated Sos1 mutation

    Science.gov (United States)

    Chen, Peng-Chieh; Wakimoto, Hiroko; Conner, David; Araki, Toshiyuki; Yuan, Tao; Roberts, Amy; Seidman, Christine E.; Bronson, Roderick; Neel, Benjamin G.; Seidman, Jonathan G.; Kucherlapati, Raju

    2010-01-01

    Noonan syndrome (NS) is an autosomal dominant genetic disorder characterized by short stature, unique facial features, and congenital heart disease. About 10%–15% of individuals with NS have mutations in son of sevenless 1 (SOS1), which encodes a RAS and RAC guanine nucleotide exchange factor (GEF). To understand the role of SOS1 in the pathogenesis of NS, we generated mice with the NS-associated Sos1E846K gain-of-function mutation. Both heterozygous and homozygous mutant mice showed many NS-associated phenotypes, including growth delay, distinctive facial dysmorphia, hematologic abnormalities, and cardiac defects. We found that the Ras/MAPK pathway as well as Rac and Stat3 were activated in the mutant hearts. These data provide in vivo molecular and cellular evidence that Sos1 is a GEF for Rac under physiological conditions and suggest that Rac and Stat3 activation might contribute to NS phenotypes. Furthermore, prenatal administration of a MEK inhibitor ameliorated the embryonic lethality, cardiac defects, and NS features of the homozygous mutant mice, demonstrating that this signaling pathway might represent a promising therapeutic target for NS. PMID:21041952

  1. The Relationships Between Policy, Boundaries and Research in Networked Learning

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Sinclair, Christine

    2016-01-01

    the books that include a selection of reworked and peer-reviewed papers from the conference. The 2014 Networked Learning Conference which was held in Edinburgh was characterised by animated dialogue on emergent influences affecting networked teaching and learning building on work established in earlier...

  2. The Impacts of Network Centrality and Self-Regulation on an E-Learning Environment with the Support of Social Network Awareness

    Science.gov (United States)

    Lin, Jian-Wei; Huang, Hsieh-Hong; Chuang, Yuh-Shy

    2015-01-01

    An e-learning environment that supports social network awareness (SNA) is a highly effective means of increasing peer interaction and assisting student learning by raising awareness of social and learning contexts of peers. Network centrality profoundly impacts student learning in an SNA-related e-learning environment. Additionally,…

  3. Description and use of the SOS Plabord code

    International Nuclear Information System (INIS)

    Morera, J.P.; Samain, A.; Capes, H.; Ghendrih, P.

    1990-09-01

    The SOS Plabord code calculates the local steady states at the plasma edge. Plasma impurities and neutral particles freed from the wall are included in the calculations. The coordinates of the two axes that limit the plasma edge layer are defined in the program. Three sorts of ions and electrons are considered. The physical parameters, the equations and the boundary conditions are given. The method chosen for solving the nonlinear differential equations and the computer program are presented [fr

  4. Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

    Science.gov (United States)

    Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff

    2016-09-14

    The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.

  5. The TENCompetence Infrastructure: A Learning Network Implementation

    Science.gov (United States)

    Vogten, Hubert; Martens, Harrie; Lemmers, Ruud

    The TENCompetence project developed a first release of a Learning Network infrastructure to support individuals, groups and organisations in professional competence development. This infrastructure Learning Network infrastructure was released as open source to the community thereby allowing users and organisations to use and contribute to this development as they see fit. The infrastructure consists of client applications providing the user experience and server components that provide the services to these clients. These services implement the domain model (Koper 2006) by provisioning the entities of the domain model (see also Sect. 18.4) and henceforth will be referenced as domain entity services.

  6. A theoretical design for learning model addressing the networked society

    DEFF Research Database (Denmark)

    Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm

    2010-01-01

    The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...

  7. Comparison between extreme learning machine and wavelet neural networks in data classification

    Science.gov (United States)

    Yahia, Siwar; Said, Salwa; Jemai, Olfa; Zaied, Mourad; Ben Amar, Chokri

    2017-03-01

    Extreme learning Machine is a well known learning algorithm in the field of machine learning. It's about a feed forward neural network with a single-hidden layer. It is an extremely fast learning algorithm with good generalization performance. In this paper, we aim to compare the Extreme learning Machine with wavelet neural networks, which is a very used algorithm. We have used six benchmark data sets to evaluate each technique. These datasets Including Wisconsin Breast Cancer, Glass Identification, Ionosphere, Pima Indians Diabetes, Wine Recognition and Iris Plant. Experimental results have shown that both extreme learning machine and wavelet neural networks have reached good results.

  8. Validating module network learning algorithms using simulated data.

    Science.gov (United States)

    Michoel, Tom; Maere, Steven; Bonnet, Eric; Joshi, Anagha; Saeys, Yvan; Van den Bulcke, Tim; Van Leemput, Koenraad; van Remortel, Piet; Kuiper, Martin; Marchal, Kathleen; Van de Peer, Yves

    2007-05-03

    In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Despite the demonstrated success of such algorithms in uncovering biologically relevant regulatory relations, further developments in the area are hampered by a lack of tools to compare the performance of alternative module network learning strategies. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators. We show that data simulators such as SynTReN are very well suited for the purpose of developing, testing and improving module network

  9. Gamification of learning deactivates the Default Mode Network

    Directory of Open Access Journals (Sweden)

    Paul Alexander Howard-Jones

    2016-01-01

    Full Text Available We hypothesised that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN and deactivation of Default Mode Network (DMN regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer, Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards. DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.

  10. Gamification of Learning Deactivates the Default Mode Network.

    Science.gov (United States)

    Howard-Jones, Paul A; Jay, Tim; Mason, Alice; Jones, Harvey

    2015-01-01

    We hypothesized that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN) and deactivation of default mode network (DMN) regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer), Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points) and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards). DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.

  11. Learning, memory, and the role of neural network architecture.

    Directory of Open Access Journals (Sweden)

    Ann M Hermundstad

    2011-06-01

    Full Text Available The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.

  12. Bayesian Inference and Online Learning in Poisson Neuronal Networks.

    Science.gov (United States)

    Huang, Yanping; Rao, Rajesh P N

    2016-08-01

    Motivated by the growing evidence for Bayesian computation in the brain, we show how a two-layer recurrent network of Poisson neurons can perform both approximate Bayesian inference and learning for any hidden Markov model. The lower-layer sensory neurons receive noisy measurements of hidden world states. The higher-layer neurons infer a posterior distribution over world states via Bayesian inference from inputs generated by sensory neurons. We demonstrate how such a neuronal network with synaptic plasticity can implement a form of Bayesian inference similar to Monte Carlo methods such as particle filtering. Each spike in a higher-layer neuron represents a sample of a particular hidden world state. The spiking activity across the neural population approximates the posterior distribution over hidden states. In this model, variability in spiking is regarded not as a nuisance but as an integral feature that provides the variability necessary for sampling during inference. We demonstrate how the network can learn the likelihood model, as well as the transition probabilities underlying the dynamics, using a Hebbian learning rule. We present results illustrating the ability of the network to perform inference and learning for arbitrary hidden Markov models.

  13. Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Hasan A. A. Al-Rawi

    2014-01-01

    Full Text Available Cognitive radio (CR enables unlicensed users (or secondary users, SUs to sense for and exploit underutilized licensed spectrum owned by the licensed users (or primary users, PUs. Reinforcement learning (RL is an artificial intelligence approach that enables a node to observe, learn, and make appropriate decisions on action selection in order to maximize network performance. Routing enables a source node to search for a least-cost route to its destination node. While there have been increasing efforts to enhance the traditional RL approach for routing in wireless networks, this research area remains largely unexplored in the domain of routing in CR networks. This paper applies RL in routing and investigates the effects of various features of RL (i.e., reward function, exploitation, and exploration, as well as learning rate through simulation. New approaches and recommendations are proposed to enhance the features in order to improve the network performance brought about by RL to routing. Simulation results show that the RL parameters of the reward function, exploitation, and exploration, as well as learning rate, must be well regulated, and the new approaches proposed in this paper improves SUs’ network performance without significantly jeopardizing PUs’ network performance, specifically SUs’ interference to PUs.

  14. CMOS/SOS RAM transient radiation upset and ''inversion'' effect investigation

    International Nuclear Information System (INIS)

    Nikiforov, A.Y.; Poljakov, I.V.

    1996-01-01

    The Complementary Metal-Oxide-Semiconductor/Silicon-on-Sapphire Random Access Memory (CMOS/SOS RAM) transient upset and inversion effect were investigated with pulsed laser, pulsed voltage generator and low-intensity light simulators. It was found that the inversion of information occurs due to memory cell photocurrents simultaneously with the power supply voltage drop transfer to memory cells outputs

  15. A Newton-type neural network learning algorithm

    International Nuclear Information System (INIS)

    Ivanov, V.V.; Puzynin, I.V.; Purehvdorzh, B.

    1993-01-01

    First- and second-order learning methods for feed-forward multilayer networks are considered. A Newton-type algorithm is proposed and compared with the common back-propagation algorithm. It is shown that the proposed algorithm provides better learning quality. Some recommendations for their usage are given. 11 refs.; 1 fig.; 1 tab

  16. Wisconsin Partnerships to Educate and Engage Public Audiences on Climate Change Topics

    Science.gov (United States)

    Mooney, M. E.; Ackerman, S.; Rowley, P.; Crowley Conn, K.

    2011-12-01

    The complexity and scale of climate change-related challenges requires more than one strategy to share meaningful information with public audiences. This presentation will discuss a few initiatives to engage the public originating from the University of Wisconsin-Madison. First, a local partnership between the Cooperative Institute for Meteorological Satellite Studies (CIMSS) and the Aldo Leopold Nature Center (ALNC), an informal learning center with a new climate change "classroom" which recently acquired a Science on a Sphere (SOS) exhibit. Second, an informal education project funded by the NOAA Office of Education coordinated by CIMSS in partnership with the national SOS Network with the goal of helping museum docents share meaningful interpretation of real-time weather and climate data. CIMSS staff has been conducting weather and climate discussions on a Magic Planet display for several years. This "mini-SOS" is powered by a solar panel on the roof, modeling the essential Sun-Earth connection and the first principle of climate literacy. However, the convenient proximity of CIMSS and ALNC provides a perfect opportunity to test "SOS-scale" talking points posted on a weekly docent blog to the benefit of the entire SOS Network. Two other Wisconsin projects of note include the Wisconsin Initiative on Climate Change Impacts, a partnership between the University and the Wisconsin Department of Natural Resources, and a pilot project between CIMSS and NOAA's National Weather Service to engage storm spotters in climate mitigation and stewardship. Ideally, the synergistic benefits and lessons learned from these collaborations can inform similar efforts in order to galvanize meaningful responses to climate change.

  17. Learning in innovation networks: Some simulation experiments

    Science.gov (United States)

    Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas

    2007-05-01

    According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.

  18. Impact of censoring on learning Bayesian networks in survival modelling.

    Science.gov (United States)

    Stajduhar, Ivan; Dalbelo-Basić, Bojana; Bogunović, Nikola

    2009-11-01

    Bayesian networks are commonly used for presenting uncertainty and covariate interactions in an easily interpretable way. Because of their efficient inference and ability to represent causal relationships, they are an excellent choice for medical decision support systems in diagnosis, treatment, and prognosis. Although good procedures for learning Bayesian networks from data have been defined, their performance in learning from censored survival data has not been widely studied. In this paper, we explore how to use these procedures to learn about possible interactions between prognostic factors and their influence on the variate of interest. We study how censoring affects the probability of learning correct Bayesian network structures. Additionally, we analyse the potential usefulness of the learnt models for predicting the time-independent probability of an event of interest. We analysed the influence of censoring with a simulation on synthetic data sampled from randomly generated Bayesian networks. We used two well-known methods for learning Bayesian networks from data: a constraint-based method and a score-based method. We compared the performance of each method under different levels of censoring to those of the naive Bayes classifier and the proportional hazards model. We did additional experiments on several datasets from real-world medical domains. The machine-learning methods treated censored cases in the data as event-free. We report and compare results for several commonly used model evaluation metrics. On average, the proportional hazards method outperformed other methods in most censoring setups. As part of the simulation study, we also analysed structural similarities of the learnt networks. Heavy censoring, as opposed to no censoring, produces up to a 5% surplus and up to 10% missing total arcs. It also produces up to 50% missing arcs that should originally be connected to the variate of interest. Presented methods for learning Bayesian networks from

  19. Networking for Learning The role of Networking in a Lifelong Learner's Professional Development

    NARCIS (Netherlands)

    Rajagopal, Kamakshi

    2016-01-01

    This dissertation discusses the role the social activity of networking plays in lifelong learners’ professional and personal continuous development. The main hypothesis of this thesis is that networking is a learning strategy for lifelong learners, in which conversations are key activities through

  20. Using Epistemic Network Analysis to understand core topics as planned learning objectives

    DEFF Research Database (Denmark)

    Allsopp, Benjamin Brink; Dreyøe, Jonas; Misfeldt, Morten

    Epistemic Network Analysis is a tool developed by the epistemic games group at the University of Wisconsin Madison for tracking the relations between concepts in students discourse (Shaffer 2017). In our current work we are applying this tool to learning objectives in teachers digital preparation....... The danish mathematics curriculum is organised in six competencies and three topics. In the recently implemented learning platforms teacher choose which of the mathematical competencies that serves as objective for a specific lesson or teaching sequence. Hence learning objectives for lessons and teaching...... sequences are defining a network of competencies, where two competencies are closely related of they often are part of the same learning objective or teaching sequence. We are currently using Epistemic Network Analysis to study these networks. In the poster we will include examples of different networks...

  1. Learning-induced pattern classification in a chaotic neural network

    International Nuclear Information System (INIS)

    Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki

    2012-01-01

    In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.

  2. Learning of N-layers neural network

    Directory of Open Access Journals (Sweden)

    Vladimír Konečný

    2005-01-01

    Full Text Available In the last decade we can observe increasing number of applications based on the Artificial Intelligence that are designed to solve problems from different areas of human activity. The reason why there is so much interest in these technologies is that the classical way of solutions does not exist or these technologies are not suitable because of their robustness. They are often used in applications like Business Intelligence that enable to obtain useful information for high-quality decision-making and to increase competitive advantage.One of the most widespread tools for the Artificial Intelligence are the artificial neural networks. Their high advantage is relative simplicity and the possibility of self-learning based on set of pattern situations.For the learning phase is the most commonly used algorithm back-propagation error (BPE. The base of BPE is the method minima of error function representing the sum of squared errors on outputs of neural net, for all patterns of the learning set. However, while performing BPE and in the first usage, we can find out that it is necessary to complete the handling of the learning factor by suitable method. The stability of the learning process and the rate of convergence depend on the selected method. In the article there are derived two functions: one function for the learning process management by the relative great error function value and the second function when the value of error function approximates to global minimum.The aim of the article is to introduce the BPE algorithm in compact matrix form for multilayer neural networks, the derivation of the learning factor handling method and the presentation of the results.

  3. Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

    Science.gov (United States)

    Gardner, Brian; Sporea, Ioana; Grüning, André

    2015-12-01

    Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.

  4. Learning the Structure of Bayesian Network from Small Amount of Data

    Directory of Open Access Journals (Sweden)

    Bogdan COCU

    2009-12-01

    Full Text Available Many areas of artificial intelligence must handling with imperfection ofinformation. One of the ways to do this is using representation and reasoning withBayesian networks. Creation of a Bayesian network consists in two stages. First stage isto design the node structure and directed links between them. Choosing of a structurefor network can be done either through empirical developing by human experts orthrough machine learning algorithm. The second stage is completion of probabilitytables for each node. Using a machine learning method is useful, especially when wehave a big amount of leaning data. But in many fields the amount of data is small,incomplete and inconsistent. In this paper, we make a case study for choosing the bestlearning method for small amount of learning data. Means more experiments we dropconclusion of using existent methods for learning a network structure.

  5. The Practices of Student Network as Cooperative Learning in Ethiopia

    Science.gov (United States)

    Reda, Weldemariam Nigusse; Hagos, Girmay Tsegay

    2015-01-01

    Student network is a teaching strategy introduced as cooperative learning to all educational levels above the upper primary schools (grade 5 and above) in Ethiopia. The study was, therefore, aimed at investigating to what extent the student network in Ethiopia is actually practiced in line with the principles of cooperative learning. Consequently,…

  6. "Getting Practical" and the National Network of Science Learning Centres

    Science.gov (United States)

    Chapman, Georgina; Langley, Mark; Skilling, Gus; Walker, John

    2011-01-01

    The national network of Science Learning Centres is a co-ordinating partner in the Getting Practical--Improving Practical Work in Science programme. The principle of training provision for the "Getting Practical" programme is a cascade model. Regional trainers employed by the national network of Science Learning Centres trained the cohort of local…

  7. Mimicking Nature´s way of organizing in industry: a network learning perspective

    DEFF Research Database (Denmark)

    Ulhøi, John Parm; Madsen, Henning

    to reconsider organisational learning as being both an internal as well as an external phenomenon. By bringing network learning into an existing interorganisational setting (such as industrial ecology) new potentials for increased learning emerge for the participating companies. The concept of network learning...

  8. Evaluating the management strategies of a forestland estate--the S-O-S approach.

    Science.gov (United States)

    Kangas, Jyrki; Kurttila, Mikko; Kajanus, Miika; Kangas, Annika

    2003-12-01

    Connecting Multiple Criteria Decision Support (MCDS) methods with SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis yields analytical priorities for the factors included in SWOT analysis and makes them commensurable. In addition, decision alternatives can be evaluated with respect to each SWOT factor. In this way, SWOT analysis provides the basic frame within which to perform analyses of decision situations. MCDS methods, in turn, assist in carrying out SWOT more analytically and in elaborating the results of the analyses so that alternative strategic decisions can be prioritized also with respect to the entire SWOT. The A'WOT analysis is an example of such hybrid methods. It makes combined use of the Analytic Hierarchy Process (AHP) and SWOT. In this study, a hybrid method of the Stochastic Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O) and SWOT is developed as an elaboration of the basic ideas of A'WOT. The method is called S-O-S (SMAA-O in SWOT). SMAA-O enables the handling of ordinal preference information as well as mixed data consisting of both ordinal and cardinal information. Using SMAA-O is enough to just rank decision elements instead of giving them cardinal preference or priority ratios as required by the most commonly used MCDS methods. Using SMAA-O, in addition to analyzing what the recommended action is under certain priorities of the criteria, enables one to analyze what kind of preferences would support each action. The S-O-S approach is illustrated by a case study, where the shareholders of a forest holding owned by a private partnership prepared the SWOT analysis. Six alternative strategies for the management of their forest holding and of old cottage located on the holding were formed. After S-O-S analyses were carried out, one alternative was found to be the most recommendable. However, different importance orders of the SWOT groups would lead to different recommendations, since three of the six alternatives

  9. Finite time convergent learning law for continuous neural networks.

    Science.gov (United States)

    Chairez, Isaac

    2014-02-01

    This paper addresses the design of a discontinuous finite time convergent learning law for neural networks with continuous dynamics. The neural network was used here to obtain a non-parametric model for uncertain systems described by a set of ordinary differential equations. The source of uncertainties was the presence of some external perturbations and poor knowledge of the nonlinear function describing the system dynamics. A new adaptive algorithm based on discontinuous algorithms was used to adjust the weights of the neural network. The adaptive algorithm was derived by means of a non-standard Lyapunov function that is lower semi-continuous and differentiable in almost the whole space. A compensator term was included in the identifier to reject some specific perturbations using a nonlinear robust algorithm. Two numerical examples demonstrated the improvements achieved by the learning algorithm introduced in this paper compared to classical schemes with continuous learning methods. The first one dealt with a benchmark problem used in the paper to explain how the discontinuous learning law works. The second one used the methane production model to show the benefits in engineering applications of the learning law proposed in this paper. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Effect of SOS-induced levels of imuABC on spontaneous and damage-induced mutagenesis in Caulobacter crescentus.

    Science.gov (United States)

    Alves, Ingrid R; Lima-Noronha, Marco A; Silva, Larissa G; Fernández-Silva, Frank S; Freitas, Aline Luiza D; Marques, Marilis V; Galhardo, Rodrigo S

    2017-11-01

    imuABC (imuAB dnaE2) genes are responsible for SOS-mutagenesis in Caulobacter crescentus and other bacterial species devoid of umuDC. In this work, we have constructed operator-constitutive mutants of the imuABC operon. We used this genetic tool to investigate the effect of SOS-induced levels of these genes upon both spontaneous and damage-induced mutagenesis. We showed that constitutive expression of imuABC does not increase spontaneous or damage-induced mutagenesis, nor increases cellular resistance to DNA-damaging agents. Nevertheless, the presence of the operator-constitutive mutation rescues mutagenesis in a recA background, indicating that imuABC are the only genes required at SOS-induced levels for translesion synthesis (TLS) in C. crescentus. Furthermore, these data also show that TLS mediated by ImuABC does not require RecA, unlike umuDC-dependent mutagenesis in E. coli. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Biologically-inspired On-chip Learning in Pulsed Neural Networks

    DEFF Research Database (Denmark)

    Lehmann, Torsten; Woodburn, Robin

    1999-01-01

    Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the "biologically-inspired" approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks, We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...

  12. Personal Learning Network Clusters: A Comparison between Mathematics and Computer Science Students

    Science.gov (United States)

    Harding, Ansie; Engelbrecht, Johann

    2015-01-01

    "Personal learning environments" (PLEs) and "personal learning networks" (PLNs) are well-known concepts. A personal learning network "cluster" is a small group of people who regularly interact academically and whose PLNs have a non-empty intersection that includes all the other members. At university level PLN…

  13. Dialogue, Language and Identity: Critical Issues for Networked Management Learning

    Science.gov (United States)

    Ferreday, Debra; Hodgson, Vivien; Jones, Chris

    2006-01-01

    This paper draws on the work of Mikhail Bakhtin and Norman Fairclough to show how dialogue is central to the construction of identity in networked management learning. The paper is based on a case study of a networked management learning course in higher education and attempts to illustrate how participants negotiate issues of difference,…

  14. Effect of an umuC-mutation on the SOS-response in E.coli cells exposed to UV-light and γ-radiation

    International Nuclear Information System (INIS)

    Komova, O.V.; Candiano, E.S.; Krasavin, E.A.

    1999-01-01

    Kinetics dependences of the SOS-induction in E.coli cells of wild type and deficient in umuC gene exposed to UV and γ-rays were analyzed. In the presence of UmuC protein SOS-induction was 3 -- 5.5 times lower and delayed for about 30 minutes after both UV and γ-rays. It was shown that the decrease of the SOS-induction in wild type cells irradiated by UV was due to more effective elimination of the photolesions from DNA by excision repair system. UmuCD-dependent inhibition of DNA replication was discussed as a possible mechanism allowing additional time for error-free repair. (author)

  15. Structural inhibition and reactivation of Escherichia coli septation by elements of the SOS and TER pathways

    International Nuclear Information System (INIS)

    Dopazo, A.; Tormo, A.; Aldea, M.; Vicente, M.

    1987-01-01

    The inhibition of cell division caused by induction of the SOS pathway in Escherichia coli structurally blocks septation, as deduced from two sets of results. Potential septation sites active at the time of SOS induction became inactivated, while those initiated during the following doubling time were active. Penicillin resistance increased in wild-type UV light-irradiated cells, a behavior similar to that observed in mutants in which structural blocks were introduced by inactivation of FtsA. Potential septation sites that have been structurally blocked by either the SOS division inhibitor, furazlocillin inhibition of PBP3, or inactivation of a TER pathway component, FtsA3, could be reactivated one doubling time after removal of the inhibitory agent in the presence of an active lon gene product. Reactivation of potential septation sites blocked by the presence of an inactivated FtsA3 was significantly lower when the lon protease was not active, suggesting that Lon plays a role in the removal of inactivated TER pathway products from the blocked potential septation sites

  16. Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

    Science.gov (United States)

    Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

    2017-03-01

    Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Practice and Learning: Spatiotemporal Differences in Thalamo-Cortical-Cerebellar Networks Engagement across Learning Phases in Schizophrenia.

    Science.gov (United States)

    Korostil, Michele; Remington, Gary; McIntosh, Anthony Randal

    2016-01-01

    Understanding how practice mediates the transition of brain-behavior networks between early and later stages of learning is constrained by the common approach to analysis of fMRI data. Prior imaging studies have mostly relied on a single scan, and parametric, task-related analyses. Our experiment incorporates a multisession fMRI lexicon-learning experiment with multivariate, whole-brain analysis to further knowledge of the distributed networks supporting practice-related learning in schizophrenia (SZ). Participants with SZ were compared with healthy control (HC) participants as they learned a novel lexicon during two fMRI scans over a several day period. All participants were trained to equal task proficiency prior to scanning. Behavioral-Partial Least Squares, a multivariate analytic approach, was used to analyze the imaging data. Permutation testing was used to determine statistical significance and bootstrap resampling to determine the reliability of the findings. With practice, HC participants transitioned to a brain-accuracy network incorporating dorsostriatal regions in late-learning stages. The SZ participants did not transition to this pattern despite comparable behavioral results. Instead, successful learners with SZ were differentiated primarily on the basis of greater engagement of perceptual and perceptual-integration brain regions. There is a different spatiotemporal unfolding of brain-learning relationships in SZ. In SZ, given the same amount of practice, the movement from networks suggestive of effortful learning toward subcortically driven procedural one differs from HC participants. Learning performance in SZ is driven by varying levels of engagement in perceptual regions, which suggests perception itself is impaired and may impact downstream, "higher level" cognition.

  18. Prefrontal Cortex Networks Shift from External to Internal Modes during Learning

    Science.gov (United States)

    Brincat, Scott L.

    2016-01-01

    As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with “internal” memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)—regions critical for sensory associations—of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11–27 Hz) oscillatory power and synchrony associated with “top-down” or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing. SIGNIFICANCE STATEMENT As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired “top-down” knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing. PMID:27629722

  19. Network Enabled - Unresolved Residual Analysis and Learning (NEURAL)

    Science.gov (United States)

    Temple, D.; Poole, M.; Camp, M.

    Since the advent of modern computational capacity, machine learning algorithms and techniques have served as a method through which to solve numerous challenging problems. However, for machine learning methods to be effective and robust, sufficient data sets must be available; specifically, in the space domain, these are generally difficult to acquire. Rapidly evolving commercial space-situational awareness companies boast the capability to collect hundreds of thousands nightly observations of resident space objects (RSOs) using a ground-based optical sensor network. This provides the ability to maintain custody of and characterize thousands of objects persistently. With this information available, novel deep learning techniques can be implemented. The technique discussed in this paper utilizes deep learning to make distinctions between nightly data collects with and without maneuvers. Implementation of these techniques will allow the data collected from optical ground-based networks to enable well informed and timely the space domain decision making.

  20. Facilitative Components of Collaborative Learning: A Review of Nine Health Research Networks.

    Science.gov (United States)

    Leroy, Lisa; Rittner, Jessica Levin; Johnson, Karin E; Gerteis, Jessie; Miller, Therese

    2017-02-01

    Collaborative research networks are increasingly used as an effective mechanism for accelerating knowledge transfer into policy and practice. This paper explored the characteristics and collaborative learning approaches of nine health research networks. Semi-structured interviews with representatives from eight diverse US health services research networks conducted between November 2012 and January 2013 and program evaluation data from a ninth. The qualitative analysis assessed each network's purpose, duration, funding sources, governance structure, methods used to foster collaboration, and barriers and facilitators to collaborative learning. The authors reviewed detailed notes from the interviews to distill salient themes. Face-to-face meetings, intentional facilitation and communication, shared vision, trust among members and willingness to work together were key facilitators of collaborative learning. Competing priorities for members, limited funding and lack of long-term support and geographic dispersion were the main barriers to coordination and collaboration across research network members. The findings illustrate the importance of collaborative learning in research networks and the challenges to evaluating the success of research network functionality. Conducting readiness assessments and developing process and outcome evaluation metrics will advance the design and show the impact of collaborative research networks. Copyright © 2017 Longwoods Publishing.

  1. The SH2 and SH3 domains of mammalian Grb2 couple the EGF receptor to the Ras activator mSos1.

    Science.gov (United States)

    Rozakis-Adcock, M; Fernley, R; Wade, J; Pawson, T; Bowtell, D

    1993-05-06

    Many tyrosine kinases, including the receptors for hormones such as epidermal growth factor (EGF), nerve growth factor and insulin, transmit intracellular signals through Ras proteins. Ligand binding to such receptors stimulates Ras guanine-nucleotide-exchange activity and increases the level of GTP-bound Ras, suggesting that these tyrosine kinases may activate a guanine-nucleotide releasing protein (GNRP). In Caenorhabditis elegans and Drosophila, genetic studies have shown that Ras activation by tyrosine kinases requires the protein Sem-5/drk, which contains a single Src-homology (SH) 2 domain and two flanking SH3 domains. Sem-5 is homologous to the mammalian protein Grb2, which binds the autophosphorylated EGF receptor and other phosphotyrosine-containing proteins such as Shc through its SH2 domain. Here we show that in rodent fibroblasts, the SH3 domains of Grb2 are bound to the proline-rich carboxy-terminal tail of mSos1, a protein homologous to Drosophila Sos. Sos is required for Ras signalling and contains a central domain related to known Ras-GNRPs. EGF stimulation induces binding of the Grb2-mSos1 complex to the autophosphorylated EGF receptor, and mSos1 phosphorylation. Grb2 therefore appears to link tyrosine kinases to a Ras-GNRP in mammalian cells.

  2. Coronary artery ectasia in Noonan syndrome: Report of an individual with SOS1 mutation and literature review.

    Science.gov (United States)

    Calcagni, Giulio; Baban, Anwar; De Luca, Enrica; Leonardi, Benedetta; Pongiglione, Giacomo; Digilio, Maria Cristina

    2016-03-01

    Noonan syndrome (NS) is the second most frequent hereditary syndrome with cardiac involvement. Pulmonary valve stenosis and hypertrophic cardiomyopathy are the most prevalent cardiovascular abnormalities. We report on a 14-year-old girl with NS due to SOS1 mutation with pulmonary stenosis and idiopathic coronary ectasia. To the best of our knowledge, this is the first report describing coronary ectasia in a patient with NS secondary to a SOS1 mutation. We include a literature review of this rare association. © 2015 Wiley Periodicals, Inc.

  3. Evelin Ilves ja kirjastus "Varrak" kinkisid SOS Lastekülale jõuludeks raamatuid

    Index Scriptorium Estoniae

    2009-01-01

    Proua Evelin Ilves ja kirjastus "Varrak" viisid 21. detsembril 2009 Keila SOS Lastekülale jõulukingiks raamatuid. Kingitud raamatud valiti välja laste soovide põhjal, nende hulgas on nii lastekirjandust kui ka teatmeteoseid

  4. Stellar parameters and H α line profile variability of Be stars in the BeSOS survey

    Science.gov (United States)

    Arcos, C.; Kanaan, S.; Chávez, J.; Vanzi, L.; Araya, I.; Curé, M.

    2018-03-01

    The Be phenomenon is present in about 20 per cent of B-type stars. Be stars show variability on a broad range of time-scales, which in most cases is related to the presence of a circumstellar disc of variable size and structure. For this reason, a time-resolved survey is highly desirable in order to understand the mechanisms of disc formation, which are still poorly understood. In addition, a complete observational sample would improve the statistical significance of the study of stellar and disc parameters. The `Be Stars Observation Survey' (BeSOS) is a survey containing reduced spectra obtained using the Pontifica Universidad Católica High Echelle Resolution Optical Spectrograph (PUCHEROS) with a spectral resolution of 17 000 in the range 4260-7300 Å. BeSOS's main objective is to offer consistent spectroscopic and time-resolved data obtained with one instrument. The user can download or plot the data and obtain stellar parameters directly from the website. We also provide a star-by-star analysis based on photometric, spectroscopic and interferometric data, as well as general information about the whole BeSOS sample. Recently, BeSOS led to the discovery of a new Be star HD 42167 and facilitated study of the V/R variation of HD 35165 and HD 120324, the steady disc of HD 110335 and the Be shell status of HD 127972. Optical spectra used in this work, as well as the stellar parameters derived, are available online at http://besos.ifa.uv.cl.

  5. Supervised dictionary learning for inferring concurrent brain networks.

    Science.gov (United States)

    Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

    2015-10-01

    Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

  6. A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.

    Science.gov (United States)

    Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi

    2015-12-01

    Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.

  7. Celebrating the Tenth Networked Learning Conference: Looking Back and Moving Forward

    DEFF Research Database (Denmark)

    de Laat, Maarten; Ryberg, Thomas

    2018-01-01

    conferences with the aim to describe some general trends and developments in networked learning research as they emerge and fade out over the years. In order to do so the authors use the proceedings of each networked learning conference (from 1998 till 2016) as a compiled dataset. This dataset forms a text...... corpus that has been analysed with Voyant tools (Sinclair and Rockwell 2016) specifically designed for analysing digital texts. Voyant tools are used to generate a set of word clouds (Cirrus) in order to visualise networked learning research-related terms that feature most frequently in each set...

  8. Assessment of Learning in Digital Interactive Social Networks: A Learning Analytics Approach

    Science.gov (United States)

    Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen

    2016-01-01

    This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable…

  9. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

    Science.gov (United States)

    Burbank, Kendra S

    2015-12-01

    The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

  10. SUSTAIN: a network model of category learning.

    Science.gov (United States)

    Love, Bradley C; Medin, Douglas L; Gureckis, Todd M

    2004-04-01

    SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.

  11. Interaction of caffeine with the SOS response pathway in Escherichia coli.

    Science.gov (United States)

    Whitney, Alyssa K; Weir, Tiffany L

    2015-01-01

    Previous studies have highlighted the antimicrobial activity of caffeine, both individually and in combination with other compounds. A proposed mechanism for caffeine's antimicrobial effects is inhibition of bacterial DNA repair pathways. The current study examines the influence of sub-lethal caffeine levels on the growth and morphology of SOS response pathway mutants of Escherichia coli. Growth inhibition after treatment with caffeine and methyl methane sulfonate (MMS), a mutagenic agent, was determined for E. coli mutants lacking key genes in the SOS response pathway. The persistence of caffeine's effects was explored by examining growth and morphology of caffeine and MMS-treated bacterial isolates in the absence of selective pressure. Caffeine significantly reduced growth of E. coli recA- and uvrA-mutants treated with MMS. However, there was no significant difference in growth between umuC-isolates treated with MMS alone and MMS in combination with caffeine after 48 h of incubation. When recA-isolates from each treatment group were grown in untreated medium, bacterial isolates that had been exposed to MMS or MMS with caffeine showed increased growth relative to controls and caffeine-treated isolates. Morphologically, recA-isolates that had been treated with caffeine and both caffeine and MMS together had begun to display filamentous growth. Caffeine treatment further reduced growth of recA- and uvrA-mutants treated with MMS, despite a non-functional SOS response pathway. However, addition of caffeine had very little effect on MMS inhibition of umuC-mutants. Thus, growth inhibition of E. coli with caffeine treatment may be driven by caffeine interaction with UmuC, but also appears to induce damage by additional mechanisms as evidenced by the additive effects of caffeine in recA- and uvrA-mutants.

  12. Artificial neuron-glia networks learning approach based on cooperative coevolution.

    Science.gov (United States)

    Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

    2015-06-01

    Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

  13. A smart-pixel holographic competitive learning network

    Science.gov (United States)

    Slagle, Timothy Michael

    Neural networks are adaptive classifiers which modify their decision boundaries based on feedback from externally- or internally-generated error signals. Optics is an attractive technology for neural network implementation because it offers the possibility of parallel, nearly instantaneous computation of the weighted neuron inputs by the propagation of light through the optical system. Using current optical device technology, system performance levels of 3 × 1011 connection updates per second can be achieved. This thesis presents an architecture for an optical competitive learning network which offers advantages over previous optical implementations, including smart-pixel-based optical neurons, phase- conjugate self-alignment of a single neuron plane, and high-density, parallel-access weight storage, interconnection, and learning in a volume hologram. The competitive learning algorithm with modifications for optical implementation is described, and algorithm simulations are performed for an example problem. The optical competitive learning architecture is then introduced. The optical system is simulated using the ``beamprop'' algorithm at the level of light propagating through the system components, and results showing competitive learning operation in agreement with the algorithm simulations are presented. The optical competitive learning requires a non-linear, non-local ``winner-take-all'' (WTA) neuron function. Custom-designed smart-pixel WTA neuron arrays were fabricated using CMOS VLSI/liquid crystal technology. Results of laboratory tests of the WTA arrays' switching characteristics, time response, and uniformity are then presented. The system uses a phase-conjugate mirror to write the self-aligning interconnection weight holograms, and energy gain is required from the reflection to minimize erasure of the existing weights. An experimental system for characterizing the PCM response is described. Useful gains of 20 were obtained with a polarization

  14. Detection of early psychotic symptoms: Validation of the Spanish version of the "Symptom Onset in Schizophrenia (SOS) inventory".

    Science.gov (United States)

    Mezquida, Gisela; Cabrera, Bibiana; Martínez-Arán, Anabel; Vieta, Eduard; Bernardo, Miguel

    2018-03-01

    The period of subclinical signs that precedes the onset of psychosis is referred to as the prodrome or high-risk mental state. The "Symptom Onset in Schizophrenia (SOS) inventory" is an instrument to characterize and date the initial symptoms of a psychotic illness. The present study aims to provide reliability and validity data for clinical and research use of the Spanish version of the SOS. Thirty-six participants with a first-episode of psychosis meeting DSM-IV criteria for schizophrenia/schizoaffective/schizophreniform disorder were administered the translated SOS and other clinical assessments. The internal validity, intrarater and interrater reliability were studied. We found strong interrater reliability. To detect the presence/absence of prodromal symptoms, Kappa coefficients ranged between 0.8 and 0.7. Similarly, the raters obtained an excellent level of agreement regarding the onset of each symptom and the duration of symptoms until first treatment (intraclass correlation coefficients between 0.9 and 1.0). Cronbach's alpha was 0.9-1.0 for all the items. The interrater reliability and concurrent validity were also excellent in both cases. This study provides robust psychometric properties of the Spanish version of the SOS. The translated version is adequate in terms of good internal validity, intrarater and interrater reliability, and is as time-efficient as the original version. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Learning in Networks for Sustainable Development

    NARCIS (Netherlands)

    Lansu, Angelique; Boon, Jo; Sloep, Peter; Van Dam-Mieras, Rietje

    2010-01-01

    The didactic model of remote internships described in this study provides the flexibility needed to support networked learners, i.e. to facilitate the development and subsequent assessment of their competences. The heterogeneity of the participants (students, employers, tutors) in the learning

  16. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

    Science.gov (United States)

    Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

    2017-04-10

    This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

  17. Analysis of SOS-Induced Spontaneous Prophage Induction in Corynebacterium glutamicum at the Single-Cell Level

    Science.gov (United States)

    Nanda, Arun M.; Heyer, Antonia; Krämer, Christina; Grünberger, Alexander; Kohlheyer, Dietrich

    2014-01-01

    The genome of the Gram-positive soil bacterium Corynebacterium glutamicum ATCC 13032 contains three integrated prophage elements (CGP1 to -3). Recently, it was shown that the large lysogenic prophage CGP3 (∼187 kbp) is excised spontaneously in a small number of cells. In this study, we provide evidence that a spontaneously induced SOS response is partly responsible for the observed spontaneous CGP3 induction. Whereas previous studies focused mainly on the induction of prophages at the population level, we analyzed the spontaneous CGP3 induction at the single-cell level using promoters of phage genes (Pint2 and Plysin) fused to reporter genes encoding fluorescent proteins. Flow-cytometric analysis revealed a spontaneous CGP3 activity in about 0.01 to 0.08% of the cells grown in standard minimal medium, which displayed a significantly reduced viability. A PrecA-eyfp promoter fusion revealed that a small fraction of C. glutamicum cells (∼0.2%) exhibited a spontaneous induction of the SOS response. Correlation of PrecA to the activity of downstream SOS genes (PdivS and PrecN) confirmed a bona fide induction of this stress response rather than stochastic gene expression. Interestingly, the reporter output of PrecA and CGP3 promoter fusions displayed a positive correlation at the single-cell level (ρ = 0.44 to 0.77). Furthermore, analysis of the PrecA-eyfp/Pint2-e2-crimson strain during growth revealed the highest percentage of spontaneous PrecA and Pint2 activity in the early exponential phase, when fast replication occurs. Based on these studies, we postulate that spontaneously occurring DNA damage induces the SOS response, which in turn triggers the induction of lysogenic prophages. PMID:24163339

  18. Factors that influence cooperation in networks for innovation and learning

    NARCIS (Netherlands)

    Sie, Rory; Bitter-Rijpkema, Marlies; Stoyanov, Slavi; Sloep, Peter

    2018-01-01

    Networked cooperation fails if the available partnerships remain opaque. A literature review and Delphi study uncovered the elements of a fruitful partnership. They relate to personality, diversity, cooperation, and management. Innovation networks and learning networks share the same cooperative

  19. The Citizen Science Program "H2O SOS: Help Heal the Ocean—Student Operated Solutions: Operation Climate Change" teaches middle and high school students about ocean threats related to climate change through hands-on activities and learning experiences in the field. This is a continuation of the Program presented last year at the Poster Session.

    Science.gov (United States)

    Weiss, N. K.; Wood, J. H.

    2017-12-01

    TThe Citizen Science Program H2O SOS: Help Heal the Ocean—Student Operated Solutions: Operation Climate Change, teaches middle and high school students about ocean threats related to climate change through hands-on activities and learning experiences in the field. During each session (in-class or after-school as a club), students build an understanding about how climate change impacts our oceans using resources provided by ExplorOcean (hands-on activities, presentations, multi-media). Through a student leadership model, students present lessons to each other, interweaving a deep learning of science, 21st century technology, communication skills, and leadership. After participating in learning experiences and activities related to 6 key climate change concepts: 1) Introduction to climate change, 2) Increased sea temperatures, 3) Ocean acidification, 4) Sea level rise, 5) Feedback mechanisms, and 6) Innovative solutions. H2O SOS- Operation Climate change participants select one focus issue and use it to design a multi-pronged campaign to increase awareness about this issue in their local community. The campaign includes social media, an interactive activity, and a visual component. All participating clubs that meet participation and action goals earn a field trip to Ocean Quest where they dive deeper into their selected issue through hands-on activities, real-world investigations, and interviews or presentations with experts. In addition to self-selected opportunities to showcase their focus issue, teams will participate in one of several key events identified by Ocean Quest.

  20. Nuclear power plant monitoring using real-time learning neural network

    International Nuclear Information System (INIS)

    Nabeshima, Kunihiko; Tuerkcan, E.; Ciftcioglu, O.

    1994-01-01

    In the present research, artificial neural network (ANN) with real-time adaptive learning is developed for the plant wide monitoring of Borssele Nuclear Power Plant (NPP). Adaptive ANN learning capability is integrated to the monitoring system so that robust and sensitive on-line monitoring is achieved in real-time environment. The major advantages provided by ANN are that system modelling is formed by means of measurement information obtained from a multi-output process system, explicit modelling is not required and the modelling is not restricted to linear systems. Also ANN can respond very fast to anomalous operational conditions. The real-time ANN learning methodology with adaptive real-time monitoring capability is described below for the wide-range and plant-wide data from an operating nuclear power plant. The layered neural network with error backpropagation algorithm for learning has three layers. The network type is auto-associative, inputs and outputs are exactly the same, using 12 plant signals. (author)

  1. Implementation of a Framework for Collaborative Social Networks in E-Learning

    Science.gov (United States)

    Maglajlic, Seid

    2016-01-01

    This paper describes the implementation of a framework for the construction and utilization of social networks in ELearning. These social networks aim to enhance collaboration between all E-Learning participants (i.e. both traineeto-trainee and trainee-to-tutor communication are targeted). E-Learning systems that include a so-called "social…

  2. Learning and innovative elements of strategy adoption rules expand cooperative network topologies.

    Science.gov (United States)

    Wang, Shijun; Szalay, Máté S; Zhang, Changshui; Csermely, Peter

    2008-04-09

    Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoner's Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.

  3. SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks

    Science.gov (United States)

    Li, Jingjing; Zhang, Yumei; Man, Jiayu; Zhou, Yun; Wu, Xiaojun

    2017-02-01

    Cooperative learning is one of the most effective teaching methods, which has been widely used. Students' mutual contact forms a cooperative learning network in this process. Our previous research demonstrated that the cooperative learning network has complex characteristics. This study aims to investigating the dynamic spreading process of the knowledge in the cooperative learning network and the inspiration of leaders in this process. To this end, complex network transmission dynamics theory is utilized to construct the knowledge dissemination model of a cooperative learning network. Based on the existing epidemic models, we propose a new susceptible-infected-susceptible-leader (SISL) model that considers both students' forgetting and leaders' inspiration, and a susceptible-infected-removed-leader (SIRL) model that considers students' interest in spreading and leaders' inspiration. The spreading threshold λcand its impact factors are analyzed. Then, numerical simulation and analysis are delivered to reveal the dynamic transmission mechanism of knowledge and leaders' role. This work is of great significance to cooperative learning theory and teaching practice. It also enriches the theory of complex network transmission dynamics.

  4. Social Networks and Performance in Distributed Learning Communities

    Science.gov (United States)

    Cadima, Rita; Ojeda, Jordi; Monguet, Josep M.

    2012-01-01

    Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this…

  5. Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory

    DEFF Research Database (Denmark)

    Lüders, Benno; Schläger, Mikkel; Korach, Aleksandra

    2017-01-01

    it easier to find unused memory location and therefor facilitates the evolution of continual learning networks. Our results suggest that augmenting evolving networks with an external memory component is not only a viable mechanism for adaptive behaviors in neuroevolution but also allows these networks...... a new task is learned. This paper takes a step in overcoming this limitation by building on the recently proposed Evolving Neural Turing Machine (ENTM) approach. In the ENTM, neural networks are augmented with an external memory component that they can write to and read from, which allows them to store...... associations quickly and over long periods of time. The results in this paper demonstrate that the ENTM is able to perform one-shot learning in reinforcement learning tasks without catastrophic forgetting of previously stored associations. Additionally, we introduce a new ENTM default jump mechanism that makes...

  6. Students' Personal Networks in Virtual and Personal Learning Environments: A Case Study in Higher Education Using Learning Analytics Approach

    Science.gov (United States)

    Casquero, Oskar; Ovelar, Ramón; Romo, Jesús; Benito, Manuel; Alberdi, Mikel

    2016-01-01

    The main objective of this paper is to analyse the effect of the affordances of a virtual learning environment and a personal learning environment (PLE) in the configuration of the students' personal networks in a higher education context. The results are discussed in light of the adaptation of the students to the learning network made up by two…

  7. Categorical Structure among Shared Features in Networks of Early-Learned Nouns

    Science.gov (United States)

    Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-01-01

    The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

  8. Developing 21st century skills through the use of student personal learning networks

    Science.gov (United States)

    Miller, Robert D.

    This research was conducted to study the development of 21st century communication, collaboration, and digital literacy skills of students at the high school level through the use of online social network tools. The importance of this study was based on evidence high school and college students are not graduating with the requisite skills of communication, collaboration, and digital literacy skills yet employers see these skills important to the success of their employees. The challenge addressed through this study was how high schools can integrate social network tools into traditional learning environments to foster the development of these 21st century skills. A qualitative research study was completed through the use of case study. One high school class in a suburban high performing town in Connecticut was selected as the research site and the sample population of eleven student participants engaged in two sets of interviews and learned through the use social network tools for one semester of the school year. The primary social network tools used were Facebook, Diigo, Google Sites, Google Docs, and Twitter. The data collected and analyzed partially supported the transfer of the theory of connectivism at the high school level. The students actively engaged in collaborative learning and research. Key results indicated a heightened engagement in learning, the development of collaborative learning and research skills, and a greater understanding of how to use social network tools for effective public communication. The use of social network tools with high school students was a positive experience that led to an increased awareness of the students as to the benefits social network tools have as a learning tool. The data supported the continued use of social network tools to develop 21st century communication, collaboration, and digital literacy skills. Future research in this area may explore emerging social network tools as well as the long term impact these tools

  9. Networking for Learning The role of Networking in a Lifelong Learner's Professional Development

    OpenAIRE

    Rajagopal, Kamakshi

    2016-01-01

    This dissertation discusses the role the social activity of networking plays in lifelong learners’ professional and personal continuous development. The main hypothesis of this thesis is that networking is a learning strategy for lifelong learners, in which conversations are key activities through which they reassess their held thoughts and make sense of their experiences together with others.

  10. Single-hidden-layer feed-forward quantum neural network based on Grover learning.

    Science.gov (United States)

    Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

    2013-09-01

    In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Enhancing Formal E-Learning with Edutainment on Social Networks

    Science.gov (United States)

    Labus, A.; Despotovic-Zrakic, M.; Radenkovic, B.; Bogdanovic, Z.; Radenkovic, M.

    2015-01-01

    This paper reports on the investigation of the possibilities of enhancing the formal e-learning process by harnessing the potential of informal game-based learning on social networks. The goal of the research is to improve the outcomes of the formal learning process through the design and implementation of an educational game on a social network…

  12. Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation

    OpenAIRE

    Chen, Tianyi; Ling, Qing; Giannakis, Georgios B.

    2017-01-01

    Network resource allocation shows revived popularity in the era of data deluge and information explosion. Existing stochastic optimization approaches fall short in attaining a desirable cost-delay tradeoff. Recognizing the central role of Lagrange multipliers in network resource allocation, a novel learn-and-adapt stochastic dual gradient (LA-SDG) method is developed in this paper to learn the sample-optimal Lagrange multiplier from historical data, and accordingly adapt the upcoming resource...

  13. A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

    Science.gov (United States)

    Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

    2015-01-01

    Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

  14. Using Social Networks to Enhance Teaching and Learning Experiences in Higher Learning Institutions

    Science.gov (United States)

    Balakrishnan, Vimala

    2014-01-01

    The paper first explores the factors that affect the use of social networks to enhance teaching and learning experiences among students and lecturers, using structured questionnaires prepared based on the Push-Pull-Mooring framework. A total of 455 students and lecturers from higher learning institutions in Malaysia participated in this study.…

  15. SOS1 gene polymorphisms are associated with gestational diabetes mellitus in a Chinese population: Results from a nested case-control study in Taiyuan, China.

    Science.gov (United States)

    Chen, Qiong; Yang, Hailan; Feng, Yongliang; Zhang, Ping; Wu, Weiwei; Li, Shuzhen; Thompson, Brian; Wang, Xin; Peng, Tingting; Wang, Fang; Xie, Bingjie; Guo, Pengge; Li, Mei; Wang, Ying; Zhao, Nan; Wang, Suping; Zhang, Yawei

    2018-03-01

    Gestational diabetes mellitus is a growing public health concern due to its large disease burden; however, the underlying pathophysiology remains unclear. Therefore, we examined the relationship between 107 single-nucleotide polymorphisms in insulin signalling pathway genes and gestational diabetes mellitus risk using a nested case-control study. The SOS1 rs7598922 GA and AA genotype were statistically significantly associated with reduced gestational diabetes mellitus risk ( p trend  = 0.0006) compared with GG genotype. At the gene level, SOS1 was statistically significantly associated with gestational diabetes mellitus risk after adjusting for multiple comparisons. Moreover, AGGA and GGGG haplotypes in SOS1 gene were associated with reduced risk of gestational diabetes mellitus. Our study provides evidence for an association between the SOS1 gene and risk of gestational diabetes mellitus; however, its role in the pathogenesis of gestational diabetes mellitus will need to be verified by further studies.

  16. Induction of sos response in Escherichia Coli cells by gamma rays

    International Nuclear Information System (INIS)

    Fuentes Lorenzo, J.L.; Padron Soler, E.; Martin Hernandez, G.; Perez Tamayo, N.; del Sol Abascal, E.R.; Almeida Varela, E.

    1996-01-01

    The kinetics of sos response induction in Escherichia Coli cells was studied by means of the gene fusion SfiA:LacZ. In these cells, the specific beta galactosidase activity and the cellular growth rate showed an exponential behaviour. The sensitivity of the GC 2181 starin to gamma irradiation is equal to Do -1= 0.00088/Gy. The beta galactosidase activity

  17. Effects of subinhibitory concentrations of antimicrobial agents on Escherichia coli O157:H7 Shiga toxin release and role of the SOS response.

    Science.gov (United States)

    Nassar, Farah J; Rahal, Elias A; Sabra, Ahmad; Matar, Ghassan M

    2013-09-01

    Treatment of Escherichia coli O157:H7 by certain antimicrobial agents often exacerbates the patient's condition by increasing either the release of preformed Shiga toxins (Stx) upon cell lysis or their production through the SOS response-triggered induction of Stx-producing prophages. Recommended subinhibitory concentrations (sub-MICs) of azithromycin (AZI), gentamicin (GEN), imipenem (IMI), and rifampicin (RIF) were evaluated in comparison to norfloxacin (NOR), an SOS-inducer, to assess the role of the SOS response in Stx release. Relative expression of recA (SOS-inducer), Q (late antitermination gene of Stx-producing prophage), stx1, and stx2 genes was assessed at two sub-MICs of the antimicrobials for two different strains of E. coli O157:H7 using reverse transcription-real-time polymerase chain reaction. Both strains at the two sub-MICs were also subjected to Western blotting for LexA protein expression and to reverse passive latex agglutination for Stx detection. For both strains at both sub-MICs, NOR and AZI caused SOS-induced Stx production (high recA, Q, and stx2 gene expression and high Stx2 production), so they should be avoided in E. coli O157:H7 treatment; however, sub-MICs of RIF and IMI induced Stx2 production in an SOS-independent manner except for one strain at the first twofold dilution below MIC of RIF where Stx2 production decreased. Moreover, GEN caused somewhat increased Stx2 production due to its mode of action rather than any effect on gene expression. The choice of antimicrobial therapy should rely on the antimicrobial mode of action, its concentration, and on the nature of the strain.

  18. Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

    Science.gov (United States)

    Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

    2018-01-01

    This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…

  19. Networked learning in, for, and with the world

    DEFF Research Database (Denmark)

    Nørgård, Rikke Toft; Mor, Yishay; Bengtsen, Søren Smedegaard

    2018-01-01

    With the so-called ‘Mode 3’ university as overarching framework (Barnett, 2004; Bengtsen & Nørgård, 2016; Barnett & Bengtsen, 2017; Nørgård, Olesen & Toft-Nielsen, 2018) this chapter considers how traditional forms of and formats for teaching and learning within higher education can be rethought,......’ in higher education. In the following sections, we will describe these transformations of university being, before considering some of the new challenges, opportunities, and potentials of teaching and learning in and through hybrid networks in the Mode 3 institution......., opportunities, and potentials to the teaching and learning that takes place at the university. Through history, and across different present national contexts and cultures, the ‘being’ of the university and its livelihood and mandate has changed (Wright, 2016; Barnett, 2018). Through these transformations where......, reconfigured, and redesigned in order to facilitate valuable, meaningful and relevant hybrid networked learning in, for, and with the world. What it means to ‘be’ a university is changing and the university is a ‘being’ that in itself is changing (Barnett, 2011), something also offering challenges...

  20. Compact pulse topology for adjustable high-voltage pulse generation using an SOS diode

    NARCIS (Netherlands)

    Driessen, A.B.J.M.; Heesch, van E.J.M.; Huiskamp, T.; Beckers, F.J.C.M.; Pemen, A.J.M.

    2014-01-01

    In this paper, a compact circuit topology is presented for pulsed power generation with a semiconductor opening switch (SOS). Such circuits require the generation of a fast forward current through the diode, followed by a reverse current that activates the recovery process. In general, magnetic

  1. Upper-Lower Bounds Candidate Sets Searching Algorithm for Bayesian Network Structure Learning

    Directory of Open Access Journals (Sweden)

    Guangyi Liu

    2014-01-01

    Full Text Available Bayesian network is an important theoretical model in artificial intelligence field and also a powerful tool for processing uncertainty issues. Considering the slow convergence speed of current Bayesian network structure learning algorithms, a fast hybrid learning method is proposed in this paper. We start with further analysis of information provided by low-order conditional independence testing, and then two methods are given for constructing graph model of network, which is theoretically proved to be upper and lower bounds of the structure space of target network, so that candidate sets are given as a result; after that a search and scoring algorithm is operated based on the candidate sets to find the final structure of the network. Simulation results show that the algorithm proposed in this paper is more efficient than similar algorithms with the same learning precision.

  2. Functional networks inference from rule-based machine learning models.

    Science.gov (United States)

    Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

    2016-01-01

    Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The

  3. RELATION BETWEEN COOPERATION AND ORGANIZATIONAL LEARNING WITH THE COMPETITIVENESS IN AN INTERORGANIZATIONAL NETWORK

    Directory of Open Access Journals (Sweden)

    Paulo Cesar Zonta

    2015-05-01

    Full Text Available The study analyzed the relationship between cooperation and organizational learning with competitiveness in a small and medium enterprises (SME network, with business of the groups of the Commercial and Industrial Association of Chapecó (ACIC. The methodology used was quantitative, with the factorial analysis. Currently, ACIC has 14 groups and 236 SME´s nucleated, developing joint activities of economic and social sustainability in Chapecó. The theoretical study raised concepts already endorsed by the scientific community on interorganizational networks, competitiveness, cooperation and organizational learning. The results demonstrated that indicators related to cooperation and learning in horizontal networks are characterized as antecedents of competitiveness in organizational networks, and that there is a positive correlation between the constructs cooperation and organizational learning with competitiveness construct. The study confirms the belief that small businesses associated in networks can increase their competitiveness, thus contributing to regional development.

  4. Managing the SOS Response for Enhanced CRISPR-Cas-Based Recombineering in E. coli through Transient Inhibition of Host RecA Activity.

    Science.gov (United States)

    Moreb, Eirik Adim; Hoover, Benjamin; Yaseen, Adam; Valyasevi, Nisakorn; Roecker, Zoe; Menacho-Melgar, Romel; Lynch, Michael D

    2017-12-15

    Phage-derived "recombineering" methods are utilized for bacterial genome editing. Recombineering results in a heterogeneous population of modified and unmodified chromosomes, and therefore selection methods, such as CRISPR-Cas9, are required to select for edited clones. Cells can evade CRISPR-Cas-induced cell death through recA-mediated induction of the SOS response. The SOS response increases RecA dependent repair as well as mutation rates through induction of the umuDC error prone polymerase. As a result, CRISPR-Cas selection is more efficient in recA mutants. We report an approach to inhibiting the SOS response and RecA activity through the expression of a mutant dominant negative form of RecA, which incorporates into wild type RecA filaments and inhibits activity. Using a plasmid-based system in which Cas9 and recA mutants are coexpressed, we can achieve increased efficiency and consistency of CRISPR-Cas9-mediated selection and recombineering in E. coli, while reducing the induction of the SOS response. To date, this approach has been shown to be independent of recA genotype and host strain lineage. Using this system, we demonstrate increased CRISPR-Cas selection efficacy with over 10 000 guides covering the E. coli chromosome. The use of dominant negative RecA or homologues may be of broad use in bacterial CRISPR-Cas-based genome editing where the SOS pathways are present.

  5. Modeling of kinetics of the inducible protein complexes of the SOS system in bacteria E. coli which realize TLS process

    International Nuclear Information System (INIS)

    Belov, O.V.

    2008-01-01

    The mathematical model describing kinetics of the inducible genes of the protein complexes, formed during SOS response in bacteria Escherichia coli is developed. Within the bounds of developed approaches the auxiliary mathematical model describing changes in concentrations of the dimers, which are the components of final protein complexes, is developed. The solutions of both models are based on the experimental data concerning expression of the basic genes of the SOS system in bacteria Escherichia coli

  6. Language Views on Social Networking Sites for Language Learning: The Case of Busuu

    Science.gov (United States)

    Álvarez Valencia, José Aldemar

    2016-01-01

    Social networking has compelled the area of computer-assisted language learning (CALL) to expand its research palette and account for new virtual ecologies that afford language learning and socialization. This study focuses on Busuu, a social networking site for language learning (SNSLL), and analyzes the views of language that are enacted through…

  7. Social Networks: Rational Learning and Information Aggregation

    Science.gov (United States)

    2009-09-01

    predecessor, Gale and Kariv (2003) who generalize the payoff equalization result of Bala and Goyal (1998) in connected social networks (discussed below...requires more notation. Using Bayes’ Rule and the assumption of equal priors on the state θ, we have that the social belief given by observing... Social Networks: Rational Learning and Information Aggregation by Ilan Lobel B.Sc., Pontif́ıcia Universidade Católica do Rio de Janeiro (2004

  8. Learning Transferable Features with Deep Adaptation Networks

    OpenAIRE

    Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

    2015-01-01

    Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

  9. Stochastic Online Learning in Dynamic Networks under Unknown Models

    Science.gov (United States)

    2016-08-02

    The key is to develop online learning strategies at each individual node. Specifically, through local information exchange with its neighbors, each...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning...Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for

  10. Perspectives on Advanced Learning Technologies and Learning Networks and Future Aerospace Workforce Environments

    Science.gov (United States)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    An overview of the advanced learning technologies is given in this presentation along with a brief description of their impact on future aerospace workforce development. The presentation is divided into five parts (see Figure 1). In the first part, a brief historical account of the evolution of learning technologies is given. The second part describes the current learning activities. The third part describes some of the future aerospace systems, as examples of high-tech engineering systems, and lists their enabling technologies. The fourth part focuses on future aerospace research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on learning technologies and learning networks.

  11. Language Learning through Social Networks: Perceptions and Reality

    Science.gov (United States)

    Lin, Chin-Hsi; Warschauer, Mark; Blake, Robert

    2016-01-01

    Language Learning Social Network Sites (LLSNSs) have attracted millions of users around the world. However, little is known about how people participate in these sites and what they learn from them. This study investigated learners' attitudes, usage, and progress in a major LLSNS through a survey of 4,174 as well as 20 individual case studies. The…

  12. Understanding the Context of Learning in an Online Social Network for Health Professionals' Informal Learning.

    Science.gov (United States)

    Li, Xin; Gray, Kathleen; Verspoor, Karin; Barnett, Stephen

    2017-01-01

    Online social networks (OSN) enable health professionals to learn informally, for example by sharing medical knowledge, or discussing practice management challenges and clinical issues. Understanding the learning context in OSN is necessary to get a complete picture of the learning process, in order to better support this type of learning. This study proposes critical contextual factors for understanding the learning context in OSN for health professionals, and demonstrates how these contextual factors can be used to analyse the learning context in a designated online learning environment for health professionals.

  13. Continuous Learning of a Multilayered Network Topology in a Video Camera Network

    Directory of Open Access Journals (Sweden)

    Zou Xiaotao

    2009-01-01

    Full Text Available Abstract A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.

  14. Continuous Learning of a Multilayered Network Topology in a Video Camera Network

    Directory of Open Access Journals (Sweden)

    Xiaotao Zou

    2009-01-01

    Full Text Available A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.

  15. Analog memristive synapse in spiking networks implementing unsupervised learning

    Directory of Open Access Journals (Sweden)

    Erika Covi

    2016-10-01

    Full Text Available Emerging brain-inspired architectures call for devices that can emulate the functionality of biological synapses in order to implement new efficient computational schemes able to solve ill-posed problems. Various devices and solutions are still under investigation and, in this respect, a challenge is opened to the researchers in the field. Indeed, the optimal candidate is a device able to reproduce the complete functionality of a synapse, i.e. the typical synaptic process underlying learning in biological systems (activity-dependent synaptic plasticity. This implies a device able to change its resistance (synaptic strength, or weight upon proper electrical stimuli (synaptic activity and showing several stable resistive states throughout its dynamic range (analog behavior. Moreover, it should be able to perform spike timing dependent plasticity (STDP, an associative homosynaptic plasticity learning rule based on the delay time between the two firing neurons the synapse is connected to. This rule is a fundamental learning protocol in state-of-art networks, because it allows unsupervised learning. Notwithstanding this fact, STDP-based unsupervised learning has been proposed several times mainly for binary synapses rather than multilevel synapses composed of many binary memristors. This paper proposes an HfO2-based analog memristor as a synaptic element which performs STDP within a small spiking neuromorphic network operating unsupervised learning for character recognition. The trained network is able to recognize five characters even in case incomplete or noisy characters are displayed and it is robust to a device-to-device variability of up to +/-30%.

  16. Analog Memristive Synapse in Spiking Networks Implementing Unsupervised Learning.

    Science.gov (United States)

    Covi, Erika; Brivio, Stefano; Serb, Alexander; Prodromakis, Themis; Fanciulli, Marco; Spiga, Sabina

    2016-01-01

    Emerging brain-inspired architectures call for devices that can emulate the functionality of biological synapses in order to implement new efficient computational schemes able to solve ill-posed problems. Various devices and solutions are still under investigation and, in this respect, a challenge is opened to the researchers in the field. Indeed, the optimal candidate is a device able to reproduce the complete functionality of a synapse, i.e., the typical synaptic process underlying learning in biological systems (activity-dependent synaptic plasticity). This implies a device able to change its resistance (synaptic strength, or weight) upon proper electrical stimuli (synaptic activity) and showing several stable resistive states throughout its dynamic range (analog behavior). Moreover, it should be able to perform spike timing dependent plasticity (STDP), an associative homosynaptic plasticity learning rule based on the delay time between the two firing neurons the synapse is connected to. This rule is a fundamental learning protocol in state-of-art networks, because it allows unsupervised learning. Notwithstanding this fact, STDP-based unsupervised learning has been proposed several times mainly for binary synapses rather than multilevel synapses composed of many binary memristors. This paper proposes an HfO 2 -based analog memristor as a synaptic element which performs STDP within a small spiking neuromorphic network operating unsupervised learning for character recognition. The trained network is able to recognize five characters even in case incomplete or noisy images are displayed and it is robust to a device-to-device variability of up to ±30%.

  17. Optimizing Knowledge Sharing In Learning Networks Through Peer Tutoring

    NARCIS (Netherlands)

    Hsiao, Amy; Brouns, Francis; Kester, Liesbeth; Sloep, Peter

    2009-01-01

    Hsiao, Y. P., Brouns, F., Kester, L., & Sloep, P. B. (2009). Optimizing Knowledge Sharing In Learning Networks Through Peer Tutoring. In D. Kinshuk, J. Sampson, J. Spector, P. Isaías, P. Barbosa & D. Ifenthaler (Eds.). Proceedings of IADIS International Conference Cognition and Exploratory Learning

  18. Informal Learning and Identity Formation in Online Social Networks

    Science.gov (United States)

    Greenhow, Christine; Robelia, Beth

    2009-01-01

    All students today are increasingly expected to develop technological fluency, digital citizenship, and other twenty-first century competencies despite wide variability in the quality of learning opportunities schools provide. Social network sites (SNSs) available via the internet may provide promising contexts for learning to supplement…

  19. Adaptive competitive learning neural networks

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abas

    2013-11-01

    Full Text Available In this paper, the adaptive competitive learning (ACL neural network algorithm is proposed. This neural network not only groups similar input feature vectors together but also determines the appropriate number of groups of these vectors. This algorithm uses a new proposed criterion referred to as the ACL criterion. This criterion evaluates different clustering structures produced by the ACL neural network for an input data set. Then, it selects the best clustering structure and the corresponding network architecture for this data set. The selected structure is composed of the minimum number of clusters that are compact and balanced in their sizes. The selected network architecture is efficient, in terms of its complexity, as it contains the minimum number of neurons. Synaptic weight vectors of these neurons represent well-separated, compact and balanced clusters in the input data set. The performance of the ACL algorithm is evaluated and compared with the performance of a recently proposed algorithm in the literature in clustering an input data set and determining its number of clusters. Results show that the ACL algorithm is more accurate and robust in both determining the number of clusters and allocating input feature vectors into these clusters than the other algorithm especially with data sets that are sparsely distributed.

  20. Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

    Science.gov (United States)

    Uddin, Raihan; Singh, Shiva M

    2017-01-01

    As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

  1. Learning automaton newtork and its dynamics. Gakushu automaton network to sono dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Quan, F [Hiroshima-Denki Institute of Technology, Hiroshima (Jpaan); Unno, F; Hirata, H [Chiba Univ., Chiba (Japan)

    1991-10-20

    In order to construct a distributed processing system having learning automata as autonomous elements, a reinforcement learning network of the automaton is proposed and it{prime}s dynamics is investigated. In this paper, it is attempted to add another level of meaning to computational cooperativity by using a reinforcement learning network with generalized leaning automata. The collection of learning automata in the team situation acts as self-interested agents that work toward improving their performance with respect to their individual preference ordering. In the global state space of the network, the case of partially synchronous stochastic process is considered. In this case, the existence of mean field is shown and a reinforcement learning algorithm which can make the dynamics on the average reinforcement trajectory is presented. This algorithm is shown to have a high convergence speed as a result of a simple experiment. 14 refs., 9 figs.

  2. Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks.

    Science.gov (United States)

    Carpenter, Gail A.

    1997-11-01

    A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multilayer perceptrons. With a winner-take-all code, the unsupervised model dART reduces to fuzzy ART and the supervised model dARTMAP reduces to fuzzy ARTMAP. With a distributed code, these networks automatically apportion learned changes according to the degree of activation of each coding node, which permits fast as well as slow learning without catastrophic forgetting. Distributed ART models replace the traditional neural network path weight with a dynamic weight equal to the rectified difference between coding node activation and an adaptive threshold. Thresholds increase monotonically during learning according to a principle of atrophy due to disuse. However, monotonic change at the synaptic level manifests itself as bidirectional change at the dynamic level, where the result of adaptation resembles long-term potentiation (LTP) for single-pulse or low frequency test inputs but can resemble long-term depression (LTD) for higher frequency test inputs. This paradoxical behavior is traced to dual computational properties of phasic and tonic coding signal components. A parallel distributed match-reset-search process also helps stabilize memory. Without the match-reset-search system, dART becomes a type of distributed competitive learning network.

  3. SOS gene induction and possible mutagenic effects of freeze-drying in Escherichia coli and Salmonella typhimurium.

    Science.gov (United States)

    Rosen, Rachel; Buchinger, Sebastian; Pfänder, Ramona; Pedhazur, Rami; Reifferscheid, Georg; Belkin, Shimshon

    2016-11-01

    We report the results of a study of the potential negative effects of the freeze-drying process, normally considered a benign means for long-term conservation of living cells and the golden standard in bacterial preservation. By monitoring gene induction using a whole-cell Escherichia coli bioreporter panel, in which diverse stress-responsive gene promoters are fused to luminescent or fluorescent reporting systems, we have demonstrated that DNA repair genes belonging to the SOS operon (recA, sulA, uvrA, umuD, and lexA) were induced upon resuscitation from the freeze-dried state, whereas other stress-responsive promoters such as grpE, katG, phoA, soxS, and sodA were not affected. This observation was confirmed by the UMU-chromotest (activation of the umuD gene promoter) in Salmonella typhimurium, as well as by real-time PCR analyses of selected E. coli SOS genes. We further show that a functional SOS operon is important in viability maintenance following resuscitation, but that at the same time, this repair system may introduce significantly higher mutation rates, comparable to those induced by high concentrations of a known mutagen. Our results also indicate that the entire freeze-drying process, rather than either freezing or drying separately, is instrumental in the induction of DNA damage.

  4. Machine Learning for ATLAS DDM Network Metrics

    CERN Document Server

    Lassnig, Mario; The ATLAS collaboration; Vamosi, Ralf

    2016-01-01

    The increasing volume of physics data is posing a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from our ongoing automation efforts. First, we describe our framework for distributed data management and network metrics, automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

  5. Do technologies have politics? The new paradigm and pedagogy in networked learning

    OpenAIRE

    Jones, Chris

    2001-01-01

    This paper explores the relationships between the technologies deployed in networked and e-Learning and the pedagogies and politics associated with them. Networked learning and the related move to e-Learning are coincident with the globalisation, commodification and massification of Higher Education. It examines the hard and soft forms of technological determinism (TD) found in the current advocacy of technological futures for Higher Education. Hard TD claims that new technologies bring about...

  6. What Online Networks Offer: "Online Network Compositions and Online Learning Experiences of Three Ethnic Groups"

    Science.gov (United States)

    Lecluijze, Suzanne Elisabeth; de Haan, Mariëtte; Ünlüsoy, Asli

    2015-01-01

    This exploratory study examines ethno-cultural diversity in youth's narratives regarding their "online" learning experiences while also investigating how these narratives can be understood from the analysis of their online network structure and composition. Based on ego-network data of 79 respondents this study compared the…

  7. Enhancing Teaching and Learning Wi-Fi Networking Using Limited Resources to Undergraduates

    Science.gov (United States)

    Sarkar, Nurul I.

    2013-01-01

    Motivating students to learn Wi-Fi (wireless fidelity) wireless networking to undergraduate students is often difficult because many students find the subject rather technical and abstract when presented in traditional lecture format. This paper focuses on the teaching and learning aspects of Wi-Fi networking using limited hardware resources. It…

  8. Energy consumption analysis for various memristive networks under different learning strategies

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Lei; Wang, Dong [Center for Brain Inspired Computing Research (CBICR), Department of Precision Instrument, Tsinghua University, Beijing 100084 (China); Zhang, Ziyang; Tang, Pei [Optical Memory National Engineering Research Center, Department of Precision Instrument, Tsinghua University, Beijing 100084 (China); Li, Guoqi, E-mail: liguoqi@mail.tsinghua.edu.cn [Center for Brain Inspired Computing Research (CBICR), Department of Precision Instrument, Tsinghua University, Beijing 100084 (China); Pei, Jing, E-mail: peij@mail.tsinghua.edu.cn [Center for Brain Inspired Computing Research (CBICR), Department of Precision Instrument, Tsinghua University, Beijing 100084 (China); Optical Memory National Engineering Research Center, Department of Precision Instrument, Tsinghua University, Beijing 100084 (China)

    2016-02-22

    Highlights: • Estimation methodology for energy consumed by memristor is established. • Energy comparisons for different learning strategies in various networks are touched. • Less-pulses and low-power-first modulation methods are energy efficient. • Proper decreasing the memristor modulation precision reduces the energy consumption. • Helpful solutions for power improving in memristive systems are proposed. - Abstract: Recently, various memristive systems emerge to emulate the efficient computing paradigm of the brain cortex; whereas, how to make them energy efficient still remains unclear, especially from an overall perspective. Here, a systematical and bottom-up energy consumption analysis is demonstrated, including the memristor device level and the network learning level. We propose an energy estimating methodology when modulating the memristive synapses, which is simulated in three typical neural networks with different synaptic structures and learning strategies for both offline and online learning. These results provide an in-depth insight to create energy efficient brain-inspired neuromorphic devices in the future.

  9. Energy consumption analysis for various memristive networks under different learning strategies

    International Nuclear Information System (INIS)

    Deng, Lei; Wang, Dong; Zhang, Ziyang; Tang, Pei; Li, Guoqi; Pei, Jing

    2016-01-01

    Highlights: • Estimation methodology for energy consumed by memristor is established. • Energy comparisons for different learning strategies in various networks are touched. • Less-pulses and low-power-first modulation methods are energy efficient. • Proper decreasing the memristor modulation precision reduces the energy consumption. • Helpful solutions for power improving in memristive systems are proposed. - Abstract: Recently, various memristive systems emerge to emulate the efficient computing paradigm of the brain cortex; whereas, how to make them energy efficient still remains unclear, especially from an overall perspective. Here, a systematical and bottom-up energy consumption analysis is demonstrated, including the memristor device level and the network learning level. We propose an energy estimating methodology when modulating the memristive synapses, which is simulated in three typical neural networks with different synaptic structures and learning strategies for both offline and online learning. These results provide an in-depth insight to create energy efficient brain-inspired neuromorphic devices in the future.

  10. Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

    Science.gov (United States)

    Karargyros, Alex; Syeda-Mahmood, Tanveer

    2018-02-01

    Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

  11. The Livermore Brain: Massive Deep Learning Networks Enabled by High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Barry Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-11-29

    The proliferation of inexpensive sensor technologies like the ubiquitous digital image sensors has resulted in the collection and sharing of vast amounts of unsorted and unexploited raw data. Companies and governments who are able to collect and make sense of large datasets to help them make better decisions more rapidly will have a competitive advantage in the information era. Machine Learning technologies play a critical role for automating the data understanding process; however, to be maximally effective, useful intermediate representations of the data are required. These representations or “features” are transformations of the raw data into a form where patterns are more easily recognized. Recent breakthroughs in Deep Learning have made it possible to learn these features from large amounts of labeled data. The focus of this project is to develop and extend Deep Learning algorithms for learning features from vast amounts of unlabeled data and to develop the HPC neural network training platform to support the training of massive network models. This LDRD project succeeded in developing new unsupervised feature learning algorithms for images and video and created a scalable neural network training toolkit for HPC. Additionally, this LDRD helped create the world’s largest freely-available image and video dataset supporting open multimedia research and used this dataset for training our deep neural networks. This research helped LLNL capture several work-for-others (WFO) projects, attract new talent, and establish collaborations with leading academic and commercial partners. Finally, this project demonstrated the successful training of the largest unsupervised image neural network using HPC resources and helped establish LLNL leadership at the intersection of Machine Learning and HPC research.

  12. Incidental and intentional learning of verbal episodic material differentially modifies functional brain networks.

    Directory of Open Access Journals (Sweden)

    Marie-Therese Kuhnert

    Full Text Available Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.

  13. Machine learning for network-based malware detection

    DEFF Research Database (Denmark)

    Stevanovic, Matija

    and based on different, mutually complementary, principles of traffic analysis. The proposed approaches rely on machine learning algorithms (MLAs) for automated and resource-efficient identification of the patterns of malicious network traffic. We evaluated the proposed methods through extensive evaluations...

  14. Online Learning of Genetic Network Programming and its Application to Prisoner’s Dilemma Game

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

    A new evolutionary model with the network structure named Genetic Network Programming (GNP) has been proposed recently. GNP, that is, an expansion of GA and GP, represents solutions as a network structure and evolves it by using “offline learning (selection, mutation, crossover)”. GNP can memorize the past action sequences in the network flow, so it can deal with Partially Observable Markov Decision Process (POMDP) well. In this paper, in order to improve the ability of GNP, Q learning (an off-policy TD control algorithm) that is one of the famous online methods is introduced for online learning of GNP. Q learning is suitable for GNP because (1) in reinforcement learning, the rewards an agent will get in the future can be estimated, (2) TD control doesn’t need much memory and can learn quickly, and (3) off-policy is suitable in order to search for an optimal solution independently of the policy. Finally, in the simulations, online learning of GNP is applied to a player for “Prisoner’s dilemma game” and its ability for online adaptation is confirmed.

  15. ‘Living' theory: a pedagogical framework for process support in networked learning

    Directory of Open Access Journals (Sweden)

    Philipa Levy

    2006-12-01

    Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.

  16. Innovating Design for Learning in the Networked Society

    DEFF Research Database (Denmark)

    Levinsen, Karin Tweddell; Nielsen, Janni

    2012-01-01

    The transition from the industrial to the knowledge or networked society has, together with the worldwide digitalization and e-permeation of our social, political and economic lives, brought challenges to the educational systems. The changes call for new key competences in terms of self-initiated......The transition from the industrial to the knowledge or networked society has, together with the worldwide digitalization and e-permeation of our social, political and economic lives, brought challenges to the educational systems. The changes call for new key competences in terms of self......-initiated and lifelong learning and digital literacy. At the same time, the implementation of new public management in educational institutions put pressure on students’ available time for studying and the qualitative outcome of learning processes. These conditions give birth to emerging tensions at the organizational...... in their practice are students who are (if at all) only familiar with the curriculum at a surface level and who expect the teachers to present digested versions of the curriculum. This chapter presents a design for teaching and learning approach in the shape of a design for learning model that aims to scaffold...

  17. Learning a Markov Logic network for supervised gene regulatory network inference.

    Science.gov (United States)

    Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

    2013-09-12

    Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a

  18. NKS/SOS-1 seminar on safety analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lauridsen, K. [Risoe National Lab., Roskilde (Denmark); Anderson, K. [Karinta-Konsult (Sweden); Pulkkinen, U. [VTT Automation (Finland)

    2001-05-01

    The report describes presentations and discussions at a seminar held at Risoe on March 22-23, 2000. The title of the seminar was NKS/SOS-1 - Safety Analysis. It dealt with issues of relevance for the safety analysis for the entire nuclear safety field (notably reactors and nuclear waste repositories). Such issues were: objectives of safety analysis, risk criteria, decision analysis, expert judgement and risk communication. In addition, one talk dealt with criteria for chemical industries in Europe. The seminar clearly showed that the concept of risk is multidimensional, which makes clarity and transparency essential elements in risk communication, and that there are issues of common concern between different applications, such as how to deal with different kinds of uncertainty and expert judgement. (au)

  19. Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

    Science.gov (United States)

    Gentry, Diana

    2017-01-01

    The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may

  20. Networks and learning: communities, practices and the metaphor of networks–a commentary

    Directory of Open Access Journals (Sweden)

    Bruce Ingraham

    2004-12-01

    Full Text Available In issue 12(1, Jones (2004 in his article ‘Networks and learning: communities, practices and the metaphor of networks' sets out to address three inter-related sets of issues: … firstly that learning technology needs to take account of the wider debate about networks and secondly that research in this field needs to address the theoretical and practical issues raised by advances in the field of networks. A third point is that the idea of the network acts as a powerful metaphor even if we are able to discount any particular theory generated in its support. The network metaphor can act as a unifying concept allowing us to bring together apparently disparate elements of the field.

  1. Bifurcation and category learning in network models of oscillating cortex

    Science.gov (United States)

    Baird, Bill

    1990-06-01

    A genetic model of oscillating cortex, which assumes “minimal” coupling justified by known anatomy, is shown to function as an associative memory, using previously developed theory. The network has explicit excitatory neurons with local inhibitory interneuron feedback that forms a set of nonlinear oscillators coupled only by long-range excitatory connections. Using a local Hebb-like learning rule for primary and higher-order synapses at the ends of the long-range connections, the system learns to store the kinds of oscillation amplitude patterns observed in olfactory and visual cortex. In olfaction, these patterns “emerge” during respiration by a pattern forming phase transition which we characterize in the model as a multiple Hopf bifurcation. We argue that these bifurcations play an important role in the operation of real digital computers and neural networks, and we use bifurcation theory to derive learning rules which analytically guarantee CAM storage of continuous periodic sequences-capacity: N/2 Fourier components for an N-node network-no “spurious” attractors.

  2. Improving Accessibility for Seniors in a Life-Long Learning Network: A Usability Study of Learning Websites

    Science.gov (United States)

    Gu, Xiaoqing; Ding, Rui; Fu, Shirong

    2011-01-01

    Senior citizens are comparatively vulnerable in accessing learning opportunities offered on the Internet due to usability problems in current web design. In an effort to build a senior-friendly learning web as a part of the Life-long Learning Network in Shanghai, usability studies of two websites currently available to Shanghai senior citizens…

  3. System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

    Science.gov (United States)

    Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

    2014-05-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

  4. SME Innovation and Learning: The Role of Networks and Crisis Events

    Science.gov (United States)

    Saunders, Mark N. K.; Gray, David E; Goregaokar, Harshita

    2014-01-01

    Purpose: The purpose of this paper is to contribute to the literature on innovation and entrepreneurial learning by exploring how SMEs learn and innovate, how they use both formal and informal learning and in particular the role of networks and crisis events within their learning experience. Design/methodology/approach: Mixed method study,…

  5. Lifelong learning of human actions with deep neural network self-organization.

    Science.gov (United States)

    Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

    2017-12-01

    Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  6. Learning to trust : network effects through time.

    NARCIS (Netherlands)

    Barrera, D.; Bunt, G. van de

    2009-01-01

    This article investigates the effects of information originating from social networks on the development of interpersonal trust relations in the context of a dialysis department of a Dutch medium-sized hospital. Hypotheses on learning effects are developed from existing theories and tested using

  7. Learning to trust: network effects through time

    NARCIS (Netherlands)

    Barrera, D.; van de Bunt, G

    2009-01-01

    This article investigates the effects of information originating from social networks on the development of interpersonal trust relations in the context of a dialysis department of a Dutch medium-sized hospital. Hypotheses on learning effects are developed from existing theories and tested using

  8. Inter-firm Networks, Organizational Learning and Knowledge Updating: An Empirical Study

    Science.gov (United States)

    Zhang, Su-rong; Wang, Wen-ping

    In the era of knowledge-based economy which information technology develops rapidly, the rate of knowledge updating has become a critical factor for enterprises to gaining competitive advantage .We build an interactional theoretical model among inter-firm networks, organizational learning and knowledge updating thereby and demonstrate it with empirical study at last. The result shows that inter-firm networks and organizational learning is the source of knowledge updating.

  9. Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition.

    Science.gov (United States)

    Valt, Christian; Klein, Christoph; Boehm, Stephan G

    2015-08-01

    Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming. © 2014 The British Psychological Society.

  10. Understanding the Construction of Personal Learning Networks to Support Non-Formal Workplace Learning of Training Professionals

    Science.gov (United States)

    Manning, Christin

    2013-01-01

    Workers in the 21st century workplace are faced with rapid and constant developments that place a heavy demand on them to continually learn beyond what the Human Resources and Training groups can meet. As a consequence, professionals must rely on non-formal learning approaches through the development of a personal learning network to keep…

  11. Statistical learning problem of artificial neural network to control roofing process

    Directory of Open Access Journals (Sweden)

    Lapidus Azariy

    2017-01-01

    Full Text Available Now software developed on the basis of artificial neural networks (ANN has been actively implemented in construction companies to support decision-making in organization and management of construction processes. ANN learning is the main stage of its development. A key question for supervised learning is how many number of training examples we need to approximate the true relationship between network inputs and output with the desired accuracy. Also designing of ANN architecture is related to learning problem known as “curse of dimensionality”. This problem is important for the study of construction process management because of the difficulty to get training data from construction sites. In previous studies the authors have designed a 4-layer feedforward ANN with a unit model of 12-5-4-1 to approximate estimation and prediction of roofing process. This paper presented the statistical learning side of created ANN with simple-error-minimization algorithm. The sample size to efficient training and the confidence interval of network outputs defined. In conclusion the authors predicted successful ANN learning in a large construction business company within a short space of time.

  12. Advanced Learning Technologies and Learning Networks and Their Impact on Future Aerospace Workforce

    Science.gov (United States)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    This document contains the proceedings of the training workshop on Advanced Learning Technologies and Learning Networks and their impact on Future Aerospace Workforce. The workshop was held at the Peninsula Workforce Development Center, Hampton, Virginia, April 2 3, 2003. The workshop was jointly sponsored by Old Dominion University and NASA. Workshop attendees came from NASA, other government agencies, industry, and universities. The objectives of the workshop were to: 1) provide broad overviews of the diverse activities related to advanced learning technologies and learning environments, and 2) identify future directions for research that have high potential for aerospace workforce development. Eighteen half-hour overviewtype presentations were made at the workshop.

  13. Energy consumption analysis for various memristive networks under different learning strategies

    Science.gov (United States)

    Deng, Lei; Wang, Dong; Zhang, Ziyang; Tang, Pei; Li, Guoqi; Pei, Jing

    2016-02-01

    Recently, various memristive systems emerge to emulate the efficient computing paradigm of the brain cortex; whereas, how to make them energy efficient still remains unclear, especially from an overall perspective. Here, a systematical and bottom-up energy consumption analysis is demonstrated, including the memristor device level and the network learning level. We propose an energy estimating methodology when modulating the memristive synapses, which is simulated in three typical neural networks with different synaptic structures and learning strategies for both offline and online learning. These results provide an in-depth insight to create energy efficient brain-inspired neuromorphic devices in the future.

  14. Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

    Science.gov (United States)

    Sadeghi, Zahra

    2016-09-01

    In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

  15. Celebrating the Tenth Networked Learning Conference: Looking Back and Moving Forward

    DEFF Research Database (Denmark)

    de Laat, Maarten; Ryberg, Thomas

    2018-01-01

    , actor network theory), learning environments and social media (e.g. LMS, MOOC, Virtual Worlds, Twitter, Facebook), technologies (e.g. phone, laptop, tablet), methodology (e.g. quantitative, qualitative) and related research in the domain of e-learning (e-learning, CSCL, TEL). The findings are placed...

  16. Personal Profiles: Enhancing Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Berlanga, Adriana; Bitter-Rijpkema, Marlies; Brouns, Francis; Sloep, Peter; Fetter, Sibren

    2009-01-01

    Berlanga, A. J., Bitter-Rijpkema, M., Brouns, F., Sloep, P. B., & Fetter, S. (2011). Personal Profiles: Enhancing Social Interaction in Learning Networks. International Journal of Web Based Communities, 7(1), 66-82.

  17. Adherence to abiotic surface induces SOS response in Escherichia coli K-12 strains under aerobic and anaerobic conditions.

    Science.gov (United States)

    Costa, Suelen B; Campos, Ana Carolina C; Pereira, Ana Claudia M; de Mattos-Guaraldi, Ana Luiza; Júnior, Raphael Hirata; Rosa, Ana Cláudia P; Asad, Lídia M B O

    2014-09-01

    During the colonization of surfaces, Escherichia coli bacteria often encounter DNA-damaging agents and these agents can induce several defence mechanisms. Base excision repair (BER) is dedicated to the repair of oxidative DNA damage caused by reactive oxygen species (ROS) generated by chemical and physical agents or by metabolism. In this work, we have evaluated whether the interaction with an abiotic surface by mutants derived from E. coli K-12 deficient in some enzymes that are part of BER causes DNA damage and associated filamentation. Moreover, we studied the role of endonuclease V (nfi gene; 1506 mutant strain) in biofilm formation. Endonuclease V is an enzyme that is involved in DNA repair of nitrosative lesions. We verified that endonuclease V is involved in biofilm formation. Our results showed more filamentation in the xthA mutant (BW9091) and triple xthA nfo nth mutant (BW535) than in the wild-type strain (AB1157). By contrast, the mutant nfi did not present filamentation in biofilm, although its wild-type strain (1466) showed rare filaments in biofilm. The filamentation of bacterial cells attaching to a surface was a consequence of SOS induction measured by the SOS chromotest. However, biofilm formation depended on the ability of the bacteria to induce the SOS response since the mutant lexA Ind(-) did not induce the SOS response and did not form any biofilm. Oxygen tension was an important factor for the interaction of the BER mutants, since these mutants exhibited decreased quantitative adherence under anaerobic conditions. However, our results showed that the presence or absence of oxygen did not affect the viability of BW9091 and BW535 strains. The nfi mutant and its wild-type did not exhibit decreased biofilm formation under anaerobic conditions. Scanning electron microscopy was also performed on the E. coli K-12 strains that had adhered to the glass, and we observed the presence of a structure similar to an extracellular matrix that depended on the

  18. Machine learning using a higher order correlation network

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Y.C.; Doolen, G.; Chen, H.H.; Sun, G.Z.; Maxwell, T.; Lee, H.Y.

    1986-01-01

    A high-order correlation tensor formalism for neural networks is described. The model can simulate auto associative, heteroassociative, as well as multiassociative memory. For the autoassociative model, simulation results show a drastic increase in the memory capacity and speed over that of the standard Hopfield-like correlation matrix methods. The possibility of using multiassociative memory for a learning universal inference network is also discussed. 9 refs., 5 figs.

  19. Overcoming uncertainty for within-network relational machine learning

    OpenAIRE

    Pfeiffer, Joseph J.

    2015-01-01

    People increasingly communicate through email and social networks to maintain friendships and conduct business, as well as share online content such as pictures, videos and products. Relational machine learning (RML) utilizes a set of observed attributes and network structure to predict corresponding labels for items; for example, to predict individuals engaged in securities fraud, we can utilize phone calls and workplace information to make joint predictions over the individuals. However, in...

  20. Home and away : learning in and learning from organisational networks in Europe

    NARCIS (Netherlands)

    Docherty, P.; Huzzard, T.; Leede, J. de

    2003-01-01

    This report is a comparative analysis of the various learning networks established within the Innoflex Project. The report recaps on the central argument underpinning Innoflex, namely that traditional ways of organising workplaces and traditional styles of management cannot achieve the commitment,

  1. Social Software: Participants' Experience Using Social Networking for Learning

    Science.gov (United States)

    Batchelder, Cecil W.

    2010-01-01

    Social networking tools used in learning provides instructional design with tools for transformative change in education. This study focused on defining the meanings and essences of social networking through the lived common experiences of 7 college students. The problem of the study was a lack of learner voice in understanding the value of social…

  2. Differential expression of SOS genes in an E. coli mutant producing unstable lexA protein enhances excision repair but inhibits mutagenesis

    International Nuclear Information System (INIS)

    Peterson, K.R.; Ganesan, A.K.; Mount, D.W.; Stanford Univ., CA)

    1986-01-01

    The SOS response is displayed following treatments which damage DNA or inhibit DNA replication. Two associated activities include enhanced capacity for DNA repair resulting from derepression of the recA, uvrA, uvrB and uvrD genes and increased mutagenesis due to derepression of recA, umuC and umuD. These changes are the consequence of the derepression of at least seventeen unlinked operons negatively regulated by LexA repressor. Following treatments that induce the SOS response, a signal molecule interacts with RecA protein, converting it to an activated form. Activated RecA protein facilitates the proteolytic cleavage of LexA repressor, which results in derepression of the regulon. The cell then enters a new physiological state during which time DNA repair processes are augmented. The lexA41 mutant of E. coli is a uv-resistant derivative of another mutant, lexA3, which produces a repressor that is not cleaved following inducing treatments. The resultant protein is unstable. Lac operon fusions to most of the genes in the SOS regulon were used to show that the various damage-inducible genes were derepressed to different extents. uvrA, B, and D were almost fully derepressed. Consistent with this finding, the rate of removal of T4 endonuclease V-sensitive sites was more rapid in the uv-irradiated lexA41 mutant than in normal cells, suggesting a more active excision repair system. We propose that the instability of the LexA41 protein reduces the intracellular concentration of repressor to a level that allows a high level of excision repair. The additional observation that SOS mutagenesis was only weakly induced in a lexA41 uvrA - mutant implies that the mutant protein partially represses one or more genes whose products promote SOS mutagenesis. 17 refs., 4 figs., 1 tab

  3. Deep learning classification in asteroseismology using an improved neural network

    DEFF Research Database (Denmark)

    Hon, Marc; Stello, Dennis; Yu, Jie

    2018-01-01

    Deep learning in the form of 1D convolutional neural networks have previously been shown to be capable of efficiently classifying the evolutionary state of oscillating red giants into red giant branch stars and helium-core burning stars by recognizing visual features in their asteroseismic...... frequency spectra. We elaborate further on the deep learning method by developing an improved convolutional neural network classifier. To make our method useful for current and future space missions such as K2, TESS, and PLATO, we train classifiers that are able to classify the evolutionary states of lower...

  4. Deep learning with convolutional neural network in radiology.

    Science.gov (United States)

    Yasaka, Koichiro; Akai, Hiroyuki; Kunimatsu, Akira; Kiryu, Shigeru; Abe, Osamu

    2018-04-01

    Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the learning process is not required. Important features can be automatically learned. Thanks to the development of hardware and software in addition to techniques regarding deep learning, application of this technique to radiological images for predicting clinically useful information, such as the detection and the evaluation of lesions, etc., are beginning to be investigated. This article illustrates basic technical knowledge regarding deep learning with CNNs along the actual course (collecting data, implementing CNNs, and training and testing phases). Pitfalls regarding this technique and how to manage them are also illustrated. We also described some advanced topics of deep learning, results of recent clinical studies, and the future directions of clinical application of deep learning techniques.

  5. Bayesian network learning for natural hazard assessments

    Science.gov (United States)

    Vogel, Kristin

    2016-04-01

    Even though quite different in occurrence and consequences, from a modelling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding. On top of the uncertainty about the modelling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Thus, for reliable natural hazard assessments it is crucial not only to capture and quantify involved uncertainties, but also to express and communicate uncertainties in an intuitive way. Decision-makers, who often find it difficult to deal with uncertainties, might otherwise return to familiar (mostly deterministic) proceedings. In the scope of the DFG research training group „NatRiskChange" we apply the probabilistic framework of Bayesian networks for diverse natural hazard and vulnerability studies. The great potential of Bayesian networks was already shown in previous natural hazard assessments. Treating each model component as random variable, Bayesian networks aim at capturing the joint distribution of all considered variables. Hence, each conditional distribution of interest (e.g. the effect of precautionary measures on damage reduction) can be inferred. The (in-)dependencies between the considered variables can be learned purely data driven or be given by experts. Even a combination of both is possible. By translating the (in-)dependences into a graph structure, Bayesian networks provide direct insights into the workings of the system and allow to learn about the underlying processes. Besides numerous studies on the topic, learning Bayesian networks from real-world data remains challenging. In previous studies, e.g. on earthquake induced ground motion and flood damage assessments, we tackled the problems arising with continuous variables

  6. Exploring the Peer Interaction Effects on Learning Achievement in a Social Learning Platform Based on Social Network Analysis

    Science.gov (United States)

    Lin, Yu-Tzu; Chen, Ming-Puu; Chang, Chia-Hu; Chang, Pu-Chen

    2017-01-01

    The benefits of social learning have been recognized by existing research. To explore knowledge distribution in social learning and its effects on learning achievement, we developed a social learning platform and explored students' behaviors of peer interactions by the proposed algorithms based on social network analysis. An empirical study was…

  7. CMOS Silicon-on-Sapphire RF Tunable Matching Networks

    Directory of Open Access Journals (Sweden)

    Chamseddine Ahmad

    2006-01-01

    Full Text Available This paper describes the design and optimization of an RF tunable network capable of matching highly mismatched loads to 50 at 1.9 GHz. Tuning was achieved using switched capacitors with low-loss, single-transistor switches. Simulations show that the performance of the matching network depends strongly on the switch performances and on the inductor losses. A 0.5 m silicon-on-sapphire (SOS CMOS technology was chosen for network implementation because of the relatively high-quality monolithic inductors achievable in the process. The matching network provides very good matching for inductive loads, and acceptable matching for highly capacitive loads. A 1 dB compression point greater than dBm was obtained for a wide range of load impedances.

  8. Self-teaching neural network learns difficult reactor control problem

    International Nuclear Information System (INIS)

    Jouse, W.C.

    1989-01-01

    A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits

  9. The role of complementary and alternative medicine (CAM) routines and rituals in men with cancer and their significant others (SOs): a qualitative investigation.

    Science.gov (United States)

    Klafke, Nadja; Eliott, Jaklin A; Olver, Ian N; Wittert, Gary A

    2014-05-01

    Complementary and alternative medicine (CAM) is frequently used in cancer patients, often with contribution of the significant others (SOs), but without consultation of healthcare professionals. This research explored how cancer patients integrate and maintain CAM use in their everyday life, and how SOs are involved in it. In this qualitative study, male participants were selected from a preceding Australian survey on CAM use in men with cancer (94 % response rate and 86 % consent rate for follow-up interview). Semistructured interviews were conducted with 26 men and 24 SOs until data saturation was reached. Interview transcripts were coded and analyzed thematically, thereby paying close attention to participants' language in use. A major theme associated with high CAM use was "CAM routines and rituals," as it was identified that men with cancer practiced CAM as (1) functional routines, (2) meaningful rituals, and (3) mental/spiritual routines or/and rituals. Regular CAM use was associated with intrapersonal and interpersonal benefits: CAM routines provided men with certainty and control, and CAM rituals functioned for cancer patients and their SOs as a means to create meaning, thereby working to counter fear and uncertainty consequent upon a diagnosis of cancer. SOs contributed most to men's uptake and maintenance of dietary-based CAM in ritualistic form resulting in interpersonal bonding and enhanced closeness. CAM routines and rituals constitute key elements in cancer patients' regular and satisfied CAM use, and they promote familial strengthening. Clinicians and physicians can convey these benefits to patient consultations, further promoting the safe and effective use of CAM.

  10. The recX gene product is involved in the SOS response in Herbaspirillum seropedicae

    International Nuclear Information System (INIS)

    Galvao, C.W.; Pedrosa, F.O.; Souza, E.M.; Yates, M.G.; Chubatsu, L.S.; Steffens, M.B.R.

    2003-01-01

    The recA and the recX genes of Herbaspirillum seropedicae were sequenced. The recX is located 359 bp downstream from recA. Sequence analysis indicated the presence of a putative operator site overlapping a probable σ 70 -dependent promoter upstream of recA and a transcription terminator downstream from recX, with no apparent promoter sequence in the intergenic region. Transcriptional analysis using lacZ promoter fusions indicated that recA expression increased three- to fourfold in the presence of methyl methanesulfonate (MMS). The roles of recA and recX genes in the SOS response were determined from studies of chromosomal mutants. The recA mutant showed the highest sensitivity to MMS and UV, and the recX mutant had an intermediate sensitivity, compared with the wild type (SMR1), confirming the essential role of the RecA protein in cell viability in the presence of mutagenic agents and also indicating a role for RecX in the SOS response. (author)

  11. The recX gene product is involved in the SOS response in Herbaspirillum seropedicae

    Energy Technology Data Exchange (ETDEWEB)

    Galvao, C.W.; Pedrosa, F.O.; Souza, E.M.; Yates, M.G.; Chubatsu, L.S.; Steffens, M.B.R. [Univ. Federal do Parana, Dept. of Biochemistry and Molecular Biology, Curitiba (Brazil)]. E-mail: steffens@bioufpr.br

    2003-02-15

    The recA and the recX genes of Herbaspirillum seropedicae were sequenced. The recX is located 359 bp downstream from recA. Sequence analysis indicated the presence of a putative operator site overlapping a probable {sigma}{sup 70}-dependent promoter upstream of recA and a transcription terminator downstream from recX, with no apparent promoter sequence in the intergenic region. Transcriptional analysis using lacZ promoter fusions indicated that recA expression increased three- to fourfold in the presence of methyl methanesulfonate (MMS). The roles of recA and recX genes in the SOS response were determined from studies of chromosomal mutants. The recA mutant showed the highest sensitivity to MMS and UV, and the recX mutant had an intermediate sensitivity, compared with the wild type (SMR1), confirming the essential role of the RecA protein in cell viability in the presence of mutagenic agents and also indicating a role for RecX in the SOS response. (author)

  12. The recX gene product is involved in the SOS response in Herbaspirillum seropedicae.

    Science.gov (United States)

    Galvão, Carolina W; Pedrosa, Fábio O; Souza, Emanuel M; Yates, M Geoffrey; Chubatsu, Leda S; Steffens, Maria Berenice R

    2003-02-01

    The recA and the recX genes of Herbaspirillum seropedicae were sequenced. The recX is located 359 bp downstream from recA. Sequence analysis indicated the presence of a putative operator site overlapping a probable sigma70-dependent promoter upstream of recA and a transcription terminator downstream from recX, with no apparent promoter sequence in the intergenic region. Transcriptional analysis using lacZ promoter fusions indicated that recA expression increased three- to fourfold in the presence of methyl methanesulfonate (MMS). The roles of recA and recX genes in the SOS response were determined from studies of chromosomal mutants. The recA mutant showed the highest sensitivity to MMS and UV, and the recX mutant had an intermediate sensitivity, compared with the wild type (SMR1), confirming the essential role of the RecA protein in cell viability in the presence of mutagenic agents and also indicating a role for RecX in the SOS response.

  13. Learning Initiatives for Network Economies in Asia (LIRNEasia ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Learning Initiatives for Network Economies in Asia (LIRNEasia) : Building Capacity in ICT Policy ... LIRNEasia seeks to build capacity for evidence-based interventions in the public policy process by persons attuned to the ... Project status.

  14. Investigation of potential genotoxic activity using the SOS Chromotest for real paracetamol wastewater and the wastewater treated by the Fenton process.

    Science.gov (United States)

    Kocak, Emel

    2015-01-01

    The potential genotoxic activity associated with high strength real paracetamol (PCT) wastewater (COD = 40,000 mg/L, TOC = 12,000 mg/L, BOD5 = 19,320 mg/L) from a large-scale drug-producing plant in the Marmara Region, was investigated in pre- and post- treated wastewater by the Fenton process (COD = 2,920 mg/L, TOC = 880 mg/L; BOD5 = 870 mg/L). The SOS Chromotest, which is based on Escherichia coli PQ37 activities, was used for the assessment of genotoxicity. The corrected induction factors (CIF) values used as quantitative measurements of the genotoxic activity were obtained from a total of four different dilutions (100, 50, 6.25, and 0.078 % v/v.) for two samples, in triplicate, to detect potentially genotoxic activities with the SOS Chromotest. The results of the SOS Chromotest demonstrated CIFmax value of 1.24, indicating that the PCT effluent (non-treated) is genotoxic. The results of the SOS Chromotest showed an CIFmax value of 1.72, indicating that the wastewater treated by Fenton process is genotoxic. The findings of this study clearly reveal that the PCT wastewater (non-treated) samples have a potentially hazardous impact on the aquatic environment before treatment, and in the wastewater that was treated by the Fenton process, genotoxicity generally increased.

  15. Structural landscape of the proline-rich domain of Sos1 nucleotide exchange factor.

    Science.gov (United States)

    McDonald, Caleb B; Bhat, Vikas; Kurouski, Dmitry; Mikles, David C; Deegan, Brian J; Seldeen, Kenneth L; Lednev, Igor K; Farooq, Amjad

    2013-01-01

    Despite its key role in mediating a plethora of cellular signaling cascades pertinent to health and disease, little is known about the structural landscape of the proline-rich (PR) domain of Sos1 guanine nucleotide exchange factor. Herein, using a battery of biophysical tools, we provide evidence that the PR domain of Sos1 is structurally disordered and adopts an extended random coil-like conformation in solution. Of particular interest is the observation that while chemical denaturation of PR domain results in the formation of a significant amount of polyproline II (PPII) helices, it has little or negligible effect on its overall size as measured by its hydrodynamic radius. Our data also show that the PR domain displays a highly dynamic conformational basin in agreement with the knowledge that the intrinsically unstructured proteins rapidly interconvert between an ensemble of conformations. Collectively, our study provides new insights into the conformational equilibrium of a key signaling molecule with important consequences on its physiological function. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Unraveling networked learning initiatives: an analytic framework

    NARCIS (Netherlands)

    Rusman, Ellen; Prinsen, Fleur; Vermeulen, Marjan

    2016-01-01

    Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences

  17. Building and Sustaining Learning Networks.

    OpenAIRE

    Bessant, John; Barnes, Justin; Morris, Mike; Kaplinsky, Raphael

    2003-01-01

    Research suggests that there are a number of potential advantages to learning in some form of network which include being able to benefit from other’s experience, being able to reduce the risks in experimentation, being able to engage in challenging reflection and in making use of peer group support. Examples of such configurations can be found in regional clusters, in sector groupings, in heterogeneous groups sharing a common topic of interest, in user groups concerned with le...

  18. The Role of Action Research in the Development of Learning Networks for Entrepreneurs

    Science.gov (United States)

    Brett, Valerie; Mullally, Martina; O'Gorman, Bill; Fuller-Love, Nerys

    2012-01-01

    Developing sustainable learning networks for entrepreneurs is the core objective of the Sustainable Learning Networks in Ireland and Wales (SLNIW) project. One research team drawn from the Centre for Enterprise Development and Regional Economy at Waterford Institute of Technology and the School of Management and Business from Aberystwyth…

  19. Threshold Learning Dynamics in Social Networks

    Science.gov (United States)

    González-Avella, Juan Carlos; Eguíluz, Victor M.; Marsili, Matteo; Vega-Redondo, Fernado; San Miguel, Maxi

    2011-01-01

    Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular), but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs. PMID:21637714

  20. Social Networking Services in E-Learning

    Science.gov (United States)

    Weber, Peter; Rothe, Hannes

    2016-01-01

    This paper is a report on the findings of a study conducted on the use of the social networking service NING in a cross-location e-learning setting named "Net Economy." We describe how we implemented NING as a fundamental part of the setting through a special phase concept and team building approach. With the help of user statistics, we…

  1. Reconstructing Causal Biological Networks through Active Learning.

    Directory of Open Access Journals (Sweden)

    Hyunghoon Cho

    Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.

  2. A Novel Text Clustering Approach Using Deep-Learning Vocabulary Network

    Directory of Open Access Journals (Sweden)

    Junkai Yi

    2017-01-01

    Full Text Available Text clustering is an effective approach to collect and organize text documents into meaningful groups for mining valuable information on the Internet. However, there exist some issues to tackle such as feature extraction and data dimension reduction. To overcome these problems, we present a novel approach named deep-learning vocabulary network. The vocabulary network is constructed based on related-word set, which contains the “cooccurrence” relations of words or terms. We replace term frequency in feature vectors with the “importance” of words in terms of vocabulary network and PageRank, which can generate more precise feature vectors to represent the meaning of text clustering. Furthermore, sparse-group deep belief network is proposed to reduce the dimensionality of feature vectors, and we introduce coverage rate for similarity measure in Single-Pass clustering. To verify the effectiveness of our work, we compare the approach to the representative algorithms, and experimental results show that feature vectors in terms of deep-learning vocabulary network have better clustering performance.

  3. On Deep Learning for Trust-Aware Recommendations in Social Networks.

    Science.gov (United States)

    Deng, Shuiguang; Huang, Longtao; Xu, Guandong; Wu, Xindong; Wu, Zhaohui

    2017-05-01

    With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to social networks, user trust information also plays an important role to obtain reliable recommendations. Although matrix factorization (MF) becomes dominant in recommender systems, the recommendation largely relies on the initialization of the user and item latent feature vectors. Aiming at addressing these challenges, we develop a novel trust-based approach for recommendation in social networks. In particular, we attempt to leverage deep learning to determinate the initialization in MF for trust-aware social recommendations and to differentiate the community effect in user's trusted friendships. A two-phase recommendation process is proposed to utilize deep learning in initialization and to synthesize the users' interests and their trusted friends' interests together with the impact of community effect for recommendations. We perform extensive experiments on real-world social network data to demonstrate the accuracy and effectiveness of our proposed approach in comparison with other state-of-the-art methods.

  4. Analytical gradients for tensor hyper-contracted MP2 and SOS-MP2 on graphical processing units

    Science.gov (United States)

    Song, Chenchen; Martínez, Todd J.

    2017-10-01

    Analytic energy gradients for tensor hyper-contraction (THC) are derived and implemented for second-order Møller-Plesset perturbation theory (MP2), with and without the scaled-opposite-spin (SOS)-MP2 approximation. By exploiting the THC factorization, the formal scaling of MP2 and SOS-MP2 gradient calculations with respect to system size is reduced to quartic and cubic, respectively. An efficient implementation has been developed that utilizes both graphics processing units and sparse tensor techniques exploiting spatial sparsity of the atomic orbitals. THC-MP2 has been applied to both geometry optimization and ab initio molecular dynamics (AIMD) simulations. The resulting energy conservation in micro-canonical AIMD demonstrates that the implementation provides accurate nuclear gradients with respect to the THC-MP2 potential energy surfaces.

  5. Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback.

    Science.gov (United States)

    Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank

    2017-02-01

    Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  6. Social Networking Sites and Addiction: Ten Lessons Learned

    OpenAIRE

    Kuss, Daria J.; Griffiths, Mark D.

    2017-01-01

    Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning onl...

  7. Multitask Learning-Based Security Event Forecast Methods for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Hui He

    2016-01-01

    Full Text Available Wireless sensor networks have strong dynamics and uncertainty, including network topological changes, node disappearance or addition, and facing various threats. First, to strengthen the detection adaptability of wireless sensor networks to various security attacks, a region similarity multitask-based security event forecast method for wireless sensor networks is proposed. This method performs topology partitioning on a large-scale sensor network and calculates the similarity degree among regional subnetworks. The trend of unknown network security events can be predicted through multitask learning of the occurrence and transmission characteristics of known network security events. Second, in case of lacking regional data, the quantitative trend of unknown regional network security events can be calculated. This study introduces a sensor network security event forecast method named Prediction Network Security Incomplete Unmarked Data (PNSIUD method to forecast missing attack data in the target region according to the known partial data in similar regions. Experimental results indicate that for an unknown security event forecast the forecast accuracy and effects of the similarity forecast algorithm are better than those of single-task learning method. At the same time, the forecast accuracy of the PNSIUD method is better than that of the traditional support vector machine method.

  8. Ensemble learning in fixed expansion layer networks for mitigating catastrophic forgetting.

    Science.gov (United States)

    Coop, Robert; Mishtal, Aaron; Arel, Itamar

    2013-10-01

    Catastrophic forgetting is a well-studied attribute of most parameterized supervised learning systems. A variation of this phenomenon, in the context of feedforward neural networks, arises when nonstationary inputs lead to loss of previously learned mappings. The majority of the schemes proposed in the literature for mitigating catastrophic forgetting were not data driven and did not scale well. We introduce the fixed expansion layer (FEL) feedforward neural network, which embeds a sparsely encoding hidden layer to help mitigate forgetting of prior learned representations. In addition, we investigate a novel framework for training ensembles of FEL networks, based on exploiting an information-theoretic measure of diversity between FEL learners, to further control undesired plasticity. The proposed methodology is demonstrated on a basic classification task, clearly emphasizing its advantages over existing techniques. The architecture proposed can be enhanced to address a range of computational intelligence tasks, such as regression problems and system control.

  9. Analytical reasoning task reveals limits of social learning in networks.

    Science.gov (United States)

    Rahwan, Iyad; Krasnoshtan, Dmytro; Shariff, Azim; Bonnefon, Jean-François

    2014-04-06

    Social learning-by observing and copying others-is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is its ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of laboratory-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias', which limits their social learning to the output, rather than the process, of their peers' reasoning-even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behaviour through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning.

  10. Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

    Science.gov (United States)

    Peng, Yefei

    2010-01-01

    An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

  11. Investigating student communities with network analysis of interactions in a physics learning center

    Directory of Open Access Journals (Sweden)

    Eric Brewe

    2012-01-01

    Full Text Available Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

  12. Investigating student communities with network analysis of interactions in a physics learning center

    Science.gov (United States)

    Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

    2012-06-01

    Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC) that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

  13. Home-School Links: Networking the Learning Community.

    Science.gov (United States)

    1996

    The topic of networking the learning community with home-school links is addressed in four papers: "Internet Access via School: Expectations of Students and Parents" (Roy Crotty); "The School Library as Community Information Gateway" (Megan Perry); "Rural Access to the Internet" (Ken Eustace); and "NetDay '96:…

  14. Dominant negative umuD mutations decreasing RecA-mediated cleavage suggest roles for intact UmuD in modulation of SOS mutagenesis

    International Nuclear Information System (INIS)

    Battista, J.R.; Ohta, Toshihiro; Nohmi, Takehiko; Sun, W.; Walker, G.C.

    1990-01-01

    The products of the SOS-regulated umuDC operon are required for most UV and chemical mutagenesis in Escherichia coli. The UmuD protein shares homology with a family of proteins that includes LexA and several bacteriophage repressors. UmuD is posttranslationally activated for its role n mutagenesis by a RecA-mediated proteolytic cleavage that yields UmuD'. A set of missense mutants of umuD was isolated and shown to encode mutant UmuD proteins that are deficient in RecA-mediated cleavage in vivo. Most of these mutations are dominant to umuD + with respect to UV mutagenesis yet do not interfere with SOS induction. Although both UmuD and UmuD' form homodimers, the authors provide evidence that they preferentially form heterodimers. The relationship of UmuD to LexA, λ repressor, and other members of the family of proteins is discussed and possible roles intact UmuD in modulating SOS mutagenesis are discussed

  15. El último urbanismo de Antonio Bonet: el poblado SOS (1970

    Directory of Open Access Journals (Sweden)

    Juan Fernando Ródenas García

    2018-04-01

    Full Text Available El poblado SOS de Aldeas Infantiles, Sant Feliu de Codines, Barcelona (1970, junto al poblado Hifrensa (realizado y los planes urbanísticos de Prat I y II (no realizados, constituyen los últimos conjuntos urbanísticos de cierto calado proyectados por Antonio Bonet, si exceptuamos su producción turística. Bonet plantea un conjunto residencial para alojar a niños huérfanos con equipamientos comunitarios educacionales y deportivos. Bonet recrea en el poblado SOS la atmósfera, a escala humana, que se respira en aquellos pueblos que aparecen fotografiados en el número 18 (1935 de la revista del GATEPAC, AC Documentos de Actividad Contemporánea, dedicado a la arquitectura popular. Pabellones encalados, bóvedas, porches, patios, muros y plataformas de piedra dispuestas como bancales agrícolas, constituyen los elementos que construyen el paisaje de un poblado de trazo moderno y formas arcaicas. Se propone el análisis de una obra inédita que, aunque no se llevó a cabo, expresa la singular lectura del autor de las condiciones de habitabilidad para niños huérfanos, del paisaje, y al mismo tiempo, la obra condensa la experiencia de Bonet como urbanista ya experimentado que en los años 70 pone a prueba con perspectiva histórica su credo teórico fundamental: la Carta de Atenas.

  16. Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm

    International Nuclear Information System (INIS)

    Yu, Lean; Wang, Shouyang; Lai, Kin Keung

    2008-01-01

    In this study, an empirical mode decomposition (EMD) based neural network ensemble learning paradigm is proposed for world crude oil spot price forecasting. For this purpose, the original crude oil spot price series were first decomposed into a finite, and often small, number of intrinsic mode functions (IMFs). Then a three-layer feed-forward neural network (FNN) model was used to model each of the extracted IMFs, so that the tendencies of these IMFs could be accurately predicted. Finally, the prediction results of all IMFs are combined with an adaptive linear neural network (ALNN), to formulate an ensemble output for the original crude oil price series. For verification and testing, two main crude oil price series, West Texas Intermediate (WTI) crude oil spot price and Brent crude oil spot price, are used to test the effectiveness of the proposed EMD-based neural network ensemble learning methodology. Empirical results obtained demonstrate attractiveness of the proposed EMD-based neural network ensemble learning paradigm. (author)

  17. Social Networking Tools and Teacher Education Learning Communities: A Case Study

    Science.gov (United States)

    Poulin, Michael T.

    2014-01-01

    Social networking tools have become an integral part of a pre-service teacher's educational experience. As a result, the educational value of social networking tools in teacher preparation programs must be examined. The specific problem addressed in this study is that the role of social networking tools in teacher education learning communities…

  18. Social Network Analysis in E-Learning Environments: A Preliminary Systematic Review

    Science.gov (United States)

    Cela, Karina L.; Sicilia, Miguel Ángel; Sánchez, Salvador

    2015-01-01

    E-learning occupies an increasingly prominent place in education. It provides the learner with a rich virtual network where he or she can exchange ideas and information and create synergies through interactions with other members of the network, whether fellow learners or teachers. Social network analysis (SNA) has proven extremely powerful at…

  19. Semantic Web, Reusable Learning Objects, Personal Learning Networks in Health: Key Pieces for Digital Health Literacy.

    Science.gov (United States)

    Konstantinidis, Stathis Th; Wharrad, Heather; Windle, Richard; Bamidis, Panagiotis D

    2017-01-01

    The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person needs.

  20. Language, Learning, and Identity in Social Networking Sites for Language Learning: The Case of Busuu

    Science.gov (United States)

    Alvarez Valencia, Jose Aldemar

    2014-01-01

    Recent progress in the discipline of computer applications such as the advent of web-based communication, afforded by the Web 2.0, has paved the way for novel applications in language learning, namely, social networking. Social networking has challenged the area of Computer Mediated Communication (CMC) to expand its research palette in order to…