WorldWideScience

Sample records for network combines fun

  1. News Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

    Science.gov (United States)

    2011-09-01

    Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

  2. FunCoup 3.0: database of genome-wide functional coupling networks.

    Science.gov (United States)

    Schmitt, Thomas; Ogris, Christoph; Sonnhammer, Erik L L

    2014-01-01

    We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.

  3. Transfusion medicine in the Formosa Fun Coast water park explosion: The role of combined tissue and blood banking.

    Science.gov (United States)

    Chang, Chih-Chun; Yeh, Chin-Chuan; Chu, Fang-Yeh

    2016-10-01

    The Formosa Fun Coast explosion, occurring in a recreational water park located in the Northern Taiwan on 27 June 2015, made 499 people burn-injured. For those who had severe burn trauma, surgical intervention and fluid resuscitation were necessary, and potential blood transfusion therapy could be initiated, especially during and after broad escharotomy. Here, we reviewed the literature regarding transfusion medicine and skin grafting as well as described the practicing experience of combined tissue and blood bank in the burn disaster in Taiwan. It was reported that patients who were severely burn-injured could receive multiple blood transfusions during hospitalization. Since the use of skin graft became a mainstay alternative for wound coverage after the early debridement of burn wounds at the beginning of the 20th century, the development of tissue banking program was initiated. In Taiwan, the tissue banking program was started in 2006. And the first combined tissue and blood bank was established in Far Eastern Memorial Hospital in 2010, equipped with the non-sterile, clean and sterile zones distinctly segregated with a unidirectional movement in the sterile area. The sterile zone was a class 10000 clean room equipped with high efficiency particulate air filter (HEPAF) and positive air pressure ventilation. The combined tissue and blood bank has been able to provide the assigned blood products and tissue graft timely and accurately, with the concepts of centralized management. In the future, the training of tissue and blood bank technicians would be continued and fortified, particularly on the regulation and quality control for further bio- and hemovigilance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Combined Heuristic Attack Strategy on Complex Networks

    Directory of Open Access Journals (Sweden)

    Marek Šimon

    2017-01-01

    Full Text Available Usually, the existence of a complex network is considered an advantage feature and efforts are made to increase its robustness against an attack. However, there exist also harmful and/or malicious networks, from social ones like spreading hoax, corruption, phishing, extremist ideology, and terrorist support up to computer networks spreading computer viruses or DDoS attack software or even biological networks of carriers or transport centers spreading disease among the population. New attack strategy can be therefore used against malicious networks, as well as in a worst-case scenario test for robustness of a useful network. A common measure of robustness of networks is their disintegration level after removal of a fraction of nodes. This robustness can be calculated as a ratio of the number of nodes of the greatest remaining network component against the number of nodes in the original network. Our paper presents a combination of heuristics optimized for an attack on a complex network to achieve its greatest disintegration. Nodes are deleted sequentially based on a heuristic criterion. Efficiency of classical attack approaches is compared to the proposed approach on Barabási-Albert, scale-free with tunable power-law exponent, and Erdős-Rényi models of complex networks and on real-world networks. Our attack strategy results in a faster disintegration, which is counterbalanced by its slightly increased computational demands.

  5. Combined natural gas and electricity network pricing

    Energy Technology Data Exchange (ETDEWEB)

    Morais, M.S.; Marangon Lima, J.W. [Universidade Federal de Itajuba, Rua Dr. Daniel de Carvalho, no. 296, Passa Quatro, Minas Gerais, CEP 37460-000 (Brazil)

    2007-04-15

    The introduction of competition to electricity generation and commercialization has been the main focus of many restructuring experiences around the world. The open access to the transmission network and a fair regulated tariff have been the keystones for the development of the electricity market. Parallel to the electricity industry, the natural gas business has great interaction with the electricity market in terms of fuel consumption and energy conversion. Given that the transmission and distribution monopolistic activities are very similar to the natural gas transportation through pipelines, economic regulation related to the natural gas network should be coherent with the transmission counterpart. This paper shows the application of the main wheeling charge methods, such as MW/gas-mile, invested related asset cost (IRAC) and Aumman-Shapley allocation, to both transmission and gas network. Stead-state equations are developed to adequate the various pricing methods. Some examples clarify the results, in terms of investments for thermal generation plants and end consumers, when combined pricing methods are used for transmission and gas networks. The paper also shows that the synergies between gas and electricity industry should be adequately considered, otherwise wrong economic signals are sent to the market players. (author)

  6. 25 Years of FUN!

    Science.gov (United States)

    Ramirez, Julio J

    2017-01-01

    Dr. Julio J. Ramirez, the founding president of the Faculty for Undergraduate Neuroscience (FUN), shared the comments below on November 13, 2016 at the 25 th Anniversary of FUN's founding, when Drs. Sally Frutiger, Stephen George, Julio Ramirez, and Dennison Smith were recognized with the Founders Award for their efforts in launching FUN in 1991.

  7. Together we have fun: native-place networks and sexual risk behaviours among Chinese male rural-urban migrants.

    Science.gov (United States)

    Yang, Xiaozhao Yousef; Kelly, Brian C; Yang, Tingzhong

    2016-05-01

    Some scholars argue that the maintenance of social networks contributes to the lower prevalence of deviant behaviours and fewer adverse health effects among migrants. But others suggest that if migrants are embedded in homogeneous networks, such networks may enable the formation of a deviant subculture that promotes risk taking. Facing this dilemma, the present study investigates how native-place networks influence sexual risk behaviours (SRBs), specifically the pursuit of commercial sex and condomless sex with sex workers, for male rural-urban migrants. Using a multi-stage sample of 1,591 male rural-urban migrants from two major migrant-influx cities within China, we assessed migrants' general friend network ties and native place networks (townsmen in migrants' local networks) and tested their associations with SRBs. Multiple logistic regression analyses indicate that native-place network ties are associated with paying for sex (OR = 1.33, p < 0.001) and condomless sex with sex workers (OR = 1.33, p < 0.001), while general friendship network ties reduce such risks (OR = 0.74, p < 0.001; OR = 0.84, p < 0.01) even after controlling for demographic background, housing conditions, length of stay, health beliefs and behaviours, and spousal companionship. Our findings suggest that native-place networks among Chinese male rural-urban migrants are associated with SRBs because homogenous networks may serve as a platform for the emergence of a deviant subculture that promotes risk behaviours. A Virtual Abstract of this paper is available at: https://www.youtube.com/watch?v=3Wg20I6j8XQ. © 2015 Foundation for the Sociology of Health & Illness.

  8. "I Don't Know What Fun Is": Examining the Intersection of Social Capital, Social Networks, and Social Recovery.

    Science.gov (United States)

    Boeri, Miriam; Gardner, Megan; Gerken, Erin; Ross, Melissa; Wheeler, Jack

    The purpose of this paper is to understand how people with problematic drug use access positive social capital. Social capital is defined as relations that provide valuable resources to individuals through participation in social networks. People with low socioeconomic status remain at a disadvantage for acquiring positive social capital, a component of recovery capital. The concept of social recovery emphasises the relational processes of recovery. In-depth life history data were collected from 29 individuals who used heroin, cocaine, crack, or methamphetamine for at least five years, have less than a high school education, and unstable employment and housing. Qualitative data were coded for social networks accessed throughout the life course, distinguished by bonding, bridging and linking social capital. Social networks included drug treatment programs; non-drug-using family and friends; religious/spiritual groups; workplace networks, and social clubs/activities. Bonding and/or bridging social capital were acquired through treatment, family and friends, religious/spiritual groups, workplaces, and social clubs. Linking social capital was not acquired through any social networks available, and many barriers to accessing mainstream social networks were found. This is a small study conducted in the US. A greater focus on social recovery is needed to achieve sustained recovery for individuals lacking access to and engagement in mainstream social networks. Social recovery is proposed as an analytical tool as well as for developing prevention, intervention, and treatment strategies.

  9. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  10. COMBINED AND STORM SEWER NETWORK MONITORING

    OpenAIRE

    Justyna Synowiecka; Ewa Burszta-Adamiak; Tomasz Konieczny; Paweł Malinowski

    2014-01-01

    Monitoring of the drainage networks is an extremely important tool used to understand the phenomena occurring in them. In an era of urbanization and increased run-off, at the expense of natural retention in the catchment, it helps to minimize the risk of local flooding and pollution. In its scope includes measurement of the amount of rainfall, with the use of rain gauges, and their measure in the sewer network, in matter of flows and channel filling, with the help of flow meters. An indispens...

  11. COMBINED AND STORM SEWER NETWORK MONITORING

    Directory of Open Access Journals (Sweden)

    Justyna Synowiecka

    2014-10-01

    Full Text Available Monitoring of the drainage networks is an extremely important tool used to understand the phenomena occurring in them. In an era of urbanization and increased run-off, at the expense of natural retention in the catchment, it helps to minimize the risk of local flooding and pollution. In its scope includes measurement of the amount of rainfall, with the use of rain gauges, and their measure in the sewer network, in matter of flows and channel filling, with the help of flow meters. An indispensable part in this step is their proper calibration calibration. In addition to ongoing monitoring of the sewer system, periodic inspections by the qualified employees of Water and Sewage Company should be done. The following article reviews measurement devices, their calibration methods, as well as the phenomena that occur during operation in the sewer network. It provides a solution for monitoring and control based on the experience of the Municipal Water and Sewage Company in Wroclaw, describing common operational problems, their causes, prevention methods and a network operation walkthrough with the improve of performance indicators KPI (Key Performance Indicators according the ECB (European Benchmarking Co-operation.

  12. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...

  13. Fun Is More Fun When Others Are Involved.

    Science.gov (United States)

    Reis, Harry T; O'Keefe, Stephanie D; Lane, Richard D

    2017-01-01

    Fun activities are commonly sought and highly desired yet their affective side has received little scrutiny. The present research investigated two features of fun in two daily diary studies and one laboratory experiment. First, we examined the affective state associated with fun experiences. Second, we investigated the social context of fun, considering whether shared fun is more enjoyable than solitary fun. Findings from these studies indicated that fun is associated with both high-activation and low-activation positive affects, and that it is enhanced when experienced with others (especially friends). However, social fun was associated with increases in high-activation but not low-activation positive affect, suggesting that social interaction emphasizes energizing affective experiences. We also found that loneliness moderated the latter effects, such that lonely individuals received a weaker boost from shared compared to solitary fun. These results add to what is known about the impact of social contexts on affective experience.

  14. Optimum Combining for Rapidly Fading Channels in Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Sonia Furman

    2003-10-01

    Full Text Available Research and technology in wireless communication systems such as radar and cellular networks have successfully implemented alternative design approaches that utilize antenna array techniques such as optimum combining, to mitigate the degradation effects of multipath in rapid fading channels. In ad hoc networks, these methods have not yet been exploited primarily due to the complexity inherent in the network's architecture. With the high demand for improved signal link quality, devices configured with omnidirectional antennas can no longer meet the growing need for link quality and spectrum efficiency. This study takes an empirical approach to determine an optimum combining antenna array based on 3 variants of interelement spacing. For rapid fading channels, the simulation results show that the performance in the network of devices retrofitted with our antenna arrays consistently exceeded those with an omnidirectional antenna. Further, with the optimum combiner, the performance increased by over 60% compared to that of an omnidirectional antenna in a rapid fading channel.

  15. Fun with Optical Fibres

    Science.gov (United States)

    Alti, Kamlesh

    2017-01-01

    Optical fibres play a very crucial role in today's technologies. Academic courses in optical fibres start at the undergraduate level. Nevertheless, student's curiosity towards optical fibres starts from the school level. In this paper, some fun experiments have been designed for both school and college students, which have some concrete…

  16. Family Fitness Fun

    Science.gov (United States)

    Being active with your family can be a fun way to get everybody moving. All of you will get the health benefits that come from being active. Plus, you’ll be a positive role model, helping your children develop good habits for an active lifetime.

  17. Django fun for Girls!

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Nowadays there is a gender gap in the IT world. Django Girls is a non-profit organization and a community that empowers and helps women to organize free, one-day programming workshops by providing tools, resources and support. Through Django Girls, we want to show our motivation in the IT world, how much fun is to code, and the things they are able to create coding. How is CERN getting involved?

  18. Combine harvester monitor system based on wireless sensor network

    Science.gov (United States)

    A measurement method based on Wireless Sensor Network (WSN) was developed to monitor the working condition of combine harvester for remote application. Three JN5139 modules were chosen for sensor data acquisition and another two as a router and a coordinator, which could create a tree topology netwo...

  19. A simple network agreement-based approach for combining evidences in a heterogeneous sensor network

    Directory of Open Access Journals (Sweden)

    Raúl Eusebio-Grande

    2015-12-01

    Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.

  20. A combined video and synchronous VSAT data network

    Science.gov (United States)

    Rowse, William

    Private Satellite Network currently operates Business Television networks for Fortune 500 companies. Several of these satellite-based networks, using VSAT technology, are combining the transmission of video with the broadcast of one-way data. This is made possible by use of the PSN Business Television Terminal which incorporates Scientific Atlanta's B-MAC system. In addition to providing high quality video, B-MAC can provide six channels of 204.5 kbs audio. Four of the six channels may be used to directly carry up to 19.2 kbs of asynchronous data or up to 56 kbs of synchronous data using circuitry jointly developed by PSN and Scientific Atlanta. The approach PSN has taken to provide one network customer in the financial industry with both video and broadcast data is described herein.

  1. 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.

  2. Fun with singing wine glasses

    Science.gov (United States)

    Boone, Christine; Galloway, Melodie; Ruiz, Michael J.

    2018-05-01

    A fun activity is presented using singing wine glasses for introductory physics students. Students tune a white wine glass and a red wine glass to as many semitones as possible by filling the glasses with the appropriate amounts of water. A smart phone app is used to measure the frequencies of equal-temperament tones. Then plots of frequency against water volume percent are made using a spreadsheet. Students can also play combinations of pitches with several glasses. A video (Ruiz 2018 Video: Singing glasses http://mjtruiz.com/ped/wineglasses/) is provided which includes an excerpt of a beautiful piece written for singing glasses and choir: Stars by Latvian composer Ēriks Ešenvalds.

  3. Fun in the Kitchen

    CERN Multimedia

    2004-01-01

    You may be familiar with Microcosm's "Fun with Physics" hands-on activities programme, which is the delight of young and old alike. In order to demonstrate the different states of matter, the "Fun with Physics"1 guides use liquid nitrogen to freeze various substances. Yoghurts, for example, are instantaneously turned into mouth-watering ice-creams! But, did you know that a distinguished chef also uses this technique? Ettore Bocchia, chef at the Grand Hotel Villa Serbelloni in Italy, uses liquid nitrogen at -196°C to freeze the dishes he prepares. Mix some yoghurts, add a soupçon of balsamic vinegar, pour in some liquid nitrogen at -196°C and the result is some delicious ice-cream. This was the recipe that Ettore Bocchia (in the centre of the picture on the left), the distinguished Italian chef, presented at the Gourmet Festival. He gave a demonstration of his skills at the St. Moritz Gourmet Festival, during the week beginning 2 February, in which the best chefs from around the world took part. CERN, whic...

  4. Putting Fun Back into Learning.

    Science.gov (United States)

    Rao, Srikumar S.

    1995-01-01

    People will learn better if they like what they are learning. Computers offer an extensive library of cases, examples, and stories that are easy to access, fun to work through, and tell students what they want to know. One example is the ASK system, a 15-module, self-study, multimedia program that is fun for trainees to use, which should enhance…

  5. Serious Simulations (for fun)

    DEFF Research Database (Denmark)

    Andersen, Christian Ulrik

    2006-01-01

    , their laws of physics and their rule structure not only belong to the game world. Incessantly and innovatively, they reach far beyond the game universe and into reality. The computer game today is the place where we not only escape reality, but also relate to reality – similar to the role of the movie......’Serious Simulations (for fun)’ deals with a dramatic change in the area of computer games. Computer games have throughout the past decades given us the opportunity to experience, tell stories and play in virtual, computer generated worlds. Today, however, the narratives of the computer games...... in the 20th century. They have become an important part of marketing, teaching, political activism, communication and information to the public. It is the language of the future, the language for and about the reality we are living in. The game simulations are still compelling and entertaining...

  6. Combined techniques for network measurements at accelerator facilities

    International Nuclear Information System (INIS)

    Pschorn, I.

    1999-01-01

    Usually network measurements at GSi (Gesellschaft fur Schwerionen forschung) are carried out by employing the Leica tachymeter TC2002K etc. Due to time constraints and the fact that GSi possesses only one of these selected, high precision total-stations, it was suddenly necessary to think about employing a Laser tracker as the major instrument for a reference network measurement. The idea was to compare the different instruments and to proof if it is possible at all to carry out a precise network measurement using a laser tracker. In the end the SMX Tracker4500 combined with Leica NA3000 for network measurements at GSi, Darmstadt and at BESSY Il, Berlin (both located in Germany) was applied. A few results are shown in the following chapters. A new technology in 3D metrology came up. Some ideas of applying these new tools in the field of accelerator measurements are given. Finally aspects of calibration and checking the performance of the employed high precision instrument are pointed out in this paper. (author)

  7. Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

    Science.gov (United States)

    Perdomo, Oscar; Arevalo, John; González, Fabio A.

    2017-11-01

    Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

  8. Promotion of active ageing combining sensor and social network data.

    Science.gov (United States)

    Bilbao, Aritz; Almeida, Aitor; López-de-Ipiña, Diego

    2016-12-01

    The increase of life expectancy in modern society has caused an increase in elderly population. Elderly people want to live independently in their home environment for as long as possible. However, as we age, our physical skills tend to worsen and our social circle tends to become smaller, something that often leads to a considerable decrease of both our physical and social activities. In this paper, we present an AAL framework developed within the SONOPA project, whose objective is to promote active ageing by combining a social network with information inferred using in-home sensors. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Combination of Bayesian Network and Overlay Model in User Modeling

    Directory of Open Access Journals (Sweden)

    Loc Nguyen

    2009-12-01

    Full Text Available The core of adaptive system is user model containing personal information such as knowledge, learning styles, goals… which is requisite for learning personalized process. There are many modeling approaches, for example: stereotype, overlay, plan recognition… but they don’t bring out the solid method for reasoning from user model. This paper introduces the statistical method that combines Bayesian network and overlay modeling so that it is able to infer user’s knowledge from evidences collected during user’s learning process.

  10. Synergy Maps: exploring compound combinations using network-based visualization.

    Science.gov (United States)

    Lewis, Richard; Guha, Rajarshi; Korcsmaros, Tamás; Bender, Andreas

    2015-01-01

    The phenomenon of super-additivity of biological response to compounds applied jointly, termed synergy, has the potential to provide many therapeutic benefits. Therefore, high throughput screening of compound combinations has recently received a great deal of attention. Large compound libraries and the feasibility of all-pairs screening can easily generate large, information-rich datasets. Previously, these datasets have been visualized using either a heat-map or a network approach-however these visualizations only partially represent the information encoded in the dataset. A new visualization technique for pairwise combination screening data, termed "Synergy Maps", is presented. In a Synergy Map, information about the synergistic interactions of compounds is integrated with information about their properties (chemical structure, physicochemical properties, bioactivity profiles) to produce a single visualization. As a result the relationships between compound and combination properties may be investigated simultaneously, and thus may afford insight into the synergy observed in the screen. An interactive web app implementation, available at http://richlewis42.github.io/synergy-maps, has been developed for public use, which may find use in navigating and filtering larger scale combination datasets. This tool is applied to a recent all-pairs dataset of anti-malarials, tested against Plasmodium falciparum, and a preliminary analysis is given as an example, illustrating the disproportionate synergism of histone deacetylase inhibitors previously described in literature, as well as suggesting new hypotheses for future investigation. Synergy Maps improve the state of the art in compound combination visualization, by simultaneously representing individual compound properties and their interactions. The web-based tool allows straightforward exploration of combination data, and easier identification of correlations between compound properties and interactions.

  11. “I Don’t Know What Fun Is”: Examining the Intersection of Social Capital, Social Networks, and Social Recovery

    Science.gov (United States)

    Boeri, Miriam; Gardner, Megan; Gerken, Erin; Ross, Melissa; Wheeler, Jack

    2016-01-01

    Purpose The purpose of this paper is to understand how people with problematic drug use access positive social capital. Social capital is defined as relations that provide valuable resources to individuals through participation in social networks. People with low socioeconomic status remain at a disadvantage for acquiring positive social capital, a component of recovery capital. The concept of social recovery emphasises the relational processes of recovery. Design/methodology/approach In-depth life history data were collected from 29 individuals who used heroin, cocaine, crack, or methamphetamine for at least five years, have less than a high school education, and unstable employment and housing. Qualitative data were coded for social networks accessed throughout the life course, distinguished by bonding, bridging and linking social capital. Findings Social networks included drug treatment programs; non-drug-using family and friends; religious/spiritual groups; workplace networks, and social clubs/activities. Bonding and/or bridging social capital were acquired through treatment, family and friends, religious/spiritual groups, workplaces, and social clubs. Linking social capital was not acquired through any social networks available, and many barriers to accessing mainstream social networks were found. Limitations This is a small study conducted in the US. Social implications A greater focus on social recovery is needed to achieve sustained recovery for individuals lacking access to and engagement in mainstream social networks. Practical implications Social recovery is proposed as an analytical tool as well as for developing prevention, intervention, and treatment strategies. PMID:27668008

  12. Xplora: making science fun!

    CERN Multimedia

    2006-01-01

    Remember those humdrum lectures in science class? Static textbook lessons have not done much to ignite excitement and interest in young children. Now the tables are turned and it is the teachers who are learning, but this time it is all about how to make science classes fun and spark the imaginations of the next generation. Xplora conference participants observing a working cloud experiment. The Xplora Conference, held at CERN from 15 to 18 June, was attended by more than 80 teachers and educators from across Europe ready to share and acquire some creative ways of teaching science. Xplora is an online reference project providing inventive techniques for teaching science in the classroom and beyond. Xplora is part of the Permanent European Resource Centre for Informal Learning (PENCIL) sponsored by the European Commission. PENCIL is comprised of 13 science centres, museums and aquariums, is partners with the University of Naples, Italy and King's College London, UK and is involved with 14 pilot projects thro...

  13. FunSAV: predicting the functional effect of single amino acid variants using a two-stage random forest model.

    Directory of Open Access Journals (Sweden)

    Mingjun Wang

    Full Text Available Single amino acid variants (SAVs are the most abundant form of known genetic variations associated with human disease. Successful prediction of the functional impact of SAVs from sequences can thus lead to an improved understanding of the underlying mechanisms of why a SAV may be associated with certain disease. In this work, we constructed a high-quality structural dataset that contained 679 high-quality protein structures with 2,048 SAVs by collecting the human genetic variant data from multiple resources and dividing them into two categories, i.e., disease-associated and neutral variants. We built a two-stage random forest (RF model, termed as FunSAV, to predict the functional effect of SAVs by combining sequence, structure and residue-contact network features with other additional features that were not explored in previous studies. Importantly, a two-step feature selection procedure was proposed to select the most important and informative features that contribute to the prediction of disease association of SAVs. In cross-validation experiments on the benchmark dataset, FunSAV achieved a good prediction performance with the area under the curve (AUC of 0.882, which is competitive with and in some cases better than other existing tools including SIFT, SNAP, Polyphen2, PANTHER, nsSNPAnalyzer and PhD-SNP. The sourcecodes of FunSAV and the datasets can be downloaded at http://sunflower.kuicr.kyoto-u.ac.jp/sjn/FunSAV.

  14. Selection combining for noncoherent decode-and-forward relay networks

    Directory of Open Access Journals (Sweden)

    Nguyen Ha

    2011-01-01

    Full Text Available Abstract This paper studies a new decode-and-forward relaying scheme for a cooperative wireless network composed of one source, K relays, and one destination and with binary frequency-shift keying modulation. A single threshold is employed to select retransmitting relays as follows: a relay retransmits to the destination if its decision variable is larger than the threshold; otherwise, it remains silent. The destination then performs selection combining for the detection of transmitted information. The average end-to-end bit-error-rate (BER is analytically determined in a closed-form expression. Based on the derived BER, the problem of choosing an optimal threshold or jointly optimal threshold and power allocation to minimize the end-to-end BER is also investigated. Both analytical and simulation results reveal that the obtained optimal threshold scheme or jointly optimal threshold and power-allocation scheme can significantly improve the BER performance compared to a previously proposed scheme.

  15. Combining morphological analysis and Bayesian networks for strategic decision support

    Directory of Open Access Journals (Sweden)

    A de Waal

    2007-12-01

    Full Text Available Morphological analysis (MA and Bayesian networks (BN are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating problem spaces. BNs are graphical models which consist of a qualitative and quantitative part. The qualitative part is a cause-and-effect, or causal graph. The quantitative part depicts the strength of the causal relationships between variables. Combining MA and BN, as two phases in a modelling process, allows us to gain the benefits of both of these methods. The strength of MA lies in defining, linking and internally evaluating the parameters of problem spaces and BN modelling allows for the definition and quantification of causal relationships between variables. Short summaries of MA and BN are provided in this paper, followed by discussions how these two computer aided methods may be combined to better facilitate modelling procedures. A simple example is presented, concerning a recent application in the field of environmental decision support.

  16. Serious computing, big fun

    CERN Multimedia

    Lohr, S

    2002-01-01

    Butterfly.net Inc company plans to announce today its Butterfly Grid, software development tools and a network for so-called massively multiplayer video games, which can be played by thousands of people at a time. One of the first applications of Grid technology outside of scientific data analysis and research (1/2 page).

  17. Going beyond Fun in STEM

    Science.gov (United States)

    Pittinsky, Todd L.; Diamante, Nicole

    2015-01-01

    The United States education system must improve its ability to produce scientists, engineers, and programmers. Despite numerous national, state, and local efforts to make the study of STEM (science, technology, engineering, and mathematics) subjects more fun in K-12, initial interest in those subjects drops off precipitously in middle and later…

  18. Fun with Singing Wine Glasses

    Science.gov (United States)

    Boone, Christine; Galloway, Melodie; Ruiz, Michael J.

    2018-01-01

    A fun activity is presented using singing wine glasses for introductory physics students. Students tune a white wine glass and a red wine glass to as many semitones as possible by filling the glasses with the appropriate amounts of water. A smart phone app is used to measure the frequencies of equal-temperament tones. Then plots of frequency…

  19. The Value of Fun in Physical Activity

    Science.gov (United States)

    El-Sherif, Jennifer L.

    2016-01-01

    According to students, fun, good grades and time with friends are the three key outcomes of physical education. A further review of fun in physical education, from the perspective of students, is included in this article. Selected responses from interviews with high school students reference fun as an important part of their experience in physical…

  20. Serious Fun: Life-Deep Learning of Koi Hobbyists

    Science.gov (United States)

    Liu, Chi-Chang

    2012-01-01

    Hobby activities can be viewed through the lens of informal, free-choice learning. A wide range of hobbies combine fun and learning-intensive practices, and can contribute to scientific literacy. Hobby learning involves clear goal orientation, persistence and effort, and often results in more richly and strongly connected knowledge; traits highly…

  1. Combining morphological analysis and Bayesian Networks for strategic decision support

    CSIR Research Space (South Africa)

    De Waal, AJ

    2007-12-01

    Full Text Available Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating...

  2. Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

    OpenAIRE

    Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

    2015-01-01

    An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solv...

  3. Fun and Games and Boredom.

    Science.gov (United States)

    Buday, Richard; Baranowski, Tom; Thompson, Debbe

    2012-08-01

    Serious videogames use entertainment to teach, train, or change behavior. What began in the 1970s as tentative attempts to create learning software is now a recognized videogame genre and an emerging health science. Although more research is needed, a growing body of literature suggests serious videogames can be effective. Support for serious videogames, however, is not universal. An informal Web search reveals numerous skeptics. Critics question serious videogames' entertainment value and, thus, their viability. "How can serious videogames attract and maintain players," the argument goes, "if they aren't as much fun as commercial titles, or even any fun at all?" This article examines the argument that, to be effective, serious videogames should be overtly fun and comparable to commercial off-the-shelf videogames. It explores differences between game developer- and researcher-led projects and discusses ways serious videogames can avoid boring and alienating players. It concludes that direct comparisons between serious and commercial game entertainment values may be misdirected.

  4. FunCoup 4: new species, data, and visualization

    OpenAIRE

    Ogris, Christoph; Guala, Dimitri; Kaduk, Mateusz; Sonnhammer, Erik L L

    2017-01-01

    Abstract This release of the FunCoup database (http://funcoup.sbc.su.se) is the fourth generation of one of the most comprehensive databases for genome-wide functional association networks. These functional associations are inferred via integrating various data types using a naive Bayesian algorithm and orthology based information transfer across different species. This approach provides high coverage of the included genomes as well as high quality of inferred interactions. In this update of ...

  5. Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

    Science.gov (United States)

    Yang, S; Wang, D

    2000-01-01

    This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

  6. Combining complex networks and data mining: Why and how

    Science.gov (United States)

    Zanin, M.; Papo, D.; Sousa, P. A.; Menasalvas, E.; Nicchi, A.; Kubik, E.; Boccaletti, S.

    2016-05-01

    The increasing power of computer technology does not dispense with the need to extract meaningful information out of data sets of ever growing size, and indeed typically exacerbates the complexity of this task. To tackle this general problem, two methods have emerged, at chronologically different times, that are now commonly used in the scientific community: data mining and complex network theory. Not only do complex network analysis and data mining share the same general goal, that of extracting information from complex systems to ultimately create a new compact quantifiable representation, but they also often address similar problems too. In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. One may then be tempted to conclude that these two fields are either largely redundant or totally antithetic. The starting point of this review is that this state of affairs should be put down to contingent rather than conceptual differences, and that these two fields can in fact advantageously be used in a synergistic manner. An overview of both fields is first provided, some fundamental concepts of which are illustrated. A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. Contexts in which the appropriate integration of complex network metrics can lead to improved classification rates with respect to classical data mining algorithms and, conversely, contexts in which data mining can be used to tackle important issues in complex network theory applications are illustrated. Finally, ways to achieve a tighter integration between complex networks and data mining, and open lines of research are discussed.

  7. Prototype real-time baseband signal combiner. [deep space network

    Science.gov (United States)

    Howard, L. D.

    1980-01-01

    The design and performance of a prototype real-time baseband signal combiner, used to enhance the received Voyager 2 spacecraft signals during the Jupiter flyby, is described. Hardware delay paths, operating programs, and firmware are discussed.

  8. Plan de empresa baking fun

    OpenAIRE

    Castiblanco Gutiérrez, Daniella María; Blanco Barrios, Andrea

    2016-01-01

    Baking fun es una empresa dedicada a la producción y comercialización de snacks saludables para niños. Sabemos que el momento de la comida no es fácil para los padres, y más aun cuando quieren alimentar con frutas y verduras a los más pequeños. Es por esto que nuestros snacks, a diferencia de los snacks tradicionales buscan combinar lo saludable con lo divertido, para que puedan alimentar balanceadamente a sus hijos mientras ellos se divierten y disfrutan nuestros snacks.

  9. Defining Fun and Seeking Flow in English Language Arts

    Science.gov (United States)

    Romano, Tom

    2009-01-01

    Students have fun with Facebook, MySpace, YouTube, and video games. They have fun text messaging, talking on cell phones, listening to iPods. They have fun at theme parks and hanging out with friends. As their teacher the author wants to introduce students to another kind of fun. This fun can be time consuming, rigorous, and fulfilling. It's the…

  10. Combining neural networks and genetic algorithms for hydrological flow forecasting

    Science.gov (United States)

    Neruda, Roman; Srejber, Jan; Neruda, Martin; Pascenko, Petr

    2010-05-01

    We present a neural network approach to rainfall-runoff modeling for small size river basins based on several time series of hourly measured data. Different neural networks are considered for short time runoff predictions (from one to six hours lead time) based on runoff and rainfall data observed in previous time steps. Correlation analysis shows that runoff data, short time rainfall history, and aggregated API values are the most significant data for the prediction. Neural models of multilayer perceptron and radial basis function networks with different numbers of units are used and compared with more traditional linear time series predictors. Out of possible 48 hours of relevant history of all the input variables, the most important ones are selected by means of input filters created by a genetic algorithm. The genetic algorithm works with population of binary encoded vectors defining input selection patterns. Standard genetic operators of two-point crossover, random bit-flipping mutation, and tournament selection were used. The evaluation of objective function of each individual consists of several rounds of building and testing a particular neural network model. The whole procedure is rather computational exacting (taking hours to days on a desktop PC), thus a high-performance mainframe computer has been used for our experiments. Results based on two years worth data from the Ploucnice river in Northern Bohemia suggest that main problems connected with this approach to modeling are ovetraining that can lead to poor generalization, and relatively small number of extreme events which makes it difficult for a model to predict the amplitude of the event. Thus, experiments with both absolute and relative runoff predictions were carried out. In general it can be concluded that the neural models show about 5 per cent improvement in terms of efficiency coefficient over liner models. Multilayer perceptrons with one hidden layer trained by back propagation algorithm and

  11. Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network

    NARCIS (Netherlands)

    Tran, Van Tung; Thobiani, Faisal Al; Tinga, Tiedo; Ball, Andrew David; Niu, Gang

    2017-01-01

    In this paper, a hybrid deep belief network is proposed to diagnose single and combined faults of suction and discharge valves in a reciprocating compressor. This hybrid integrates the deep belief network structured by multiple stacked restricted Boltzmann machines for pre-training and simplified

  12. Combining epidemiological and genetic networks signifies the importance of early treatment in HIV-1 transmission.

    Science.gov (United States)

    Zarrabi, Narges; Prosperi, Mattia; Belleman, Robert G; Colafigli, Manuela; De Luca, Andrea; Sloot, Peter M A

    2012-01-01

    Inferring disease transmission networks is important in epidemiology in order to understand and prevent the spread of infectious diseases. Reconstruction of the infection transmission networks requires insight into viral genome data as well as social interactions. For the HIV-1 epidemic, current research either uses genetic information of patients' virus to infer the past infection events or uses statistics of sexual interactions to model the network structure of viral spreading. Methods for a reliable reconstruction of HIV-1 transmission dynamics, taking into account both molecular and societal data are still lacking. The aim of this study is to combine information from both genetic and epidemiological scales to characterize and analyse a transmission network of the HIV-1 epidemic in central Italy.We introduce a novel filter-reduction method to build a network of HIV infected patients based on their social and treatment information. The network is then combined with a genetic network, to infer a hypothetical infection transmission network. We apply this method to a cohort study of HIV-1 infected patients in central Italy and find that patients who are highly connected in the network have longer untreated infection periods. We also find that the network structures for homosexual males and heterosexual populations are heterogeneous, consisting of a majority of 'peripheral nodes' that have only a few sexual interactions and a minority of 'hub nodes' that have many sexual interactions. Inferring HIV-1 transmission networks using this novel combined approach reveals remarkable correlations between high out-degree individuals and longer untreated infection periods. These findings signify the importance of early treatment and support the potential benefit of wide population screening, management of early diagnoses and anticipated antiretroviral treatment to prevent viral transmission and spread. The approach presented here for reconstructing HIV-1 transmission networks

  13. Fun and friends : the impact of workplace fun and constituent attachment on turnover in a hospitality context

    OpenAIRE

    Tews, Michael J.; Michel, John W.; Allen, David G.

    2014-01-01

    Extending the growing body of research on fun in the workplace, this article reports on a study examinining the relationship between fun and employee turnover. Specifically, this research focused on the influence of three forms of fun on turnover – fun activities, coworker socializing and manager support for fun. With a sample of 296 servers from 20 units of a national restaurant chain in the US, coworker socializing and manager support for fun were demonstrated to be significantly related to...

  14. Combining region- and network-level brain-behavior relationships in a structural equation model.

    Science.gov (United States)

    Bolt, Taylor; Prince, Emily B; Nomi, Jason S; Messinger, Daniel; Llabre, Maria M; Uddin, Lucina Q

    2018-01-15

    Brain-behavior associations in fMRI studies are typically restricted to a single level of analysis: either a circumscribed brain region-of-interest (ROI) or a larger network of brain regions. However, this common practice may not always account for the interdependencies among ROIs of the same network or potentially unique information at the ROI-level, respectively. To account for both sources of information, we combined measurement and structural components of structural equation modeling (SEM) approaches to empirically derive networks from ROI activity, and to assess the association of both individual ROIs and their respective whole-brain activation networks with task performance using three large task-fMRI datasets and two separate brain parcellation schemes. The results for working memory and relational tasks revealed that well-known ROI-performance associations are either non-significant or reversed when accounting for the ROI's common association with its corresponding network, and that the network as a whole is instead robustly associated with task performance. The results for the arithmetic task revealed that in certain cases, an ROI can be robustly associated with task performance, even when accounting for its associated network. The SEM framework described in this study provides researchers additional flexibility in testing brain-behavior relationships, as well as a principled way to combine ROI- and network-levels of analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. FUN3D Manual: 13.3

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2018-01-01

    This manual describes the installation and execution of FUN3D version 13.3, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  16. FUN3D Manual: 12.8

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2015-01-01

    This manual describes the installation and execution of FUN3D version 12.8, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  17. FUN3D Manual: 13.1

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2017-01-01

    This manual describes the installation and execution of FUN3D version 13.1, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  18. FUN3D Manual: 13.2

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, William L.; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2017-01-01

    This manual describes the installation and execution of FUN3D version 13.2, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  19. FUN3D Manual: 12.9

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2016-01-01

    This manual describes the installation and execution of FUN3D version 12.9, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  20. FUN3D Manual: 13.0

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bill; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2016-01-01

    This manual describes the installation and execution of FUN3D version 13.0, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  1. FUN3D Manual: 12.7

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; hide

    2015-01-01

    This manual describes the installation and execution of FUN3D version 12.7, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  2. The FUN of identifying gene function in bacterial pathogens; insights from Salmonella functional genomics.

    Science.gov (United States)

    Hammarlöf, Disa L; Canals, Rocío; Hinton, Jay C D

    2013-10-01

    The availability of thousands of genome sequences of bacterial pathogens poses a particular challenge because each genome contains hundreds of genes of unknown function (FUN). How can we easily discover which FUN genes encode important virulence factors? One solution is to combine two different functional genomic approaches. First, transcriptomics identifies bacterial FUN genes that show differential expression during the process of mammalian infection. Second, global mutagenesis identifies individual FUN genes that the pathogen requires to cause disease. The intersection of these datasets can reveal a small set of candidate genes most likely to encode novel virulence attributes. We demonstrate this approach with the Salmonella infection model, and propose that a similar strategy could be used for other bacterial pathogens. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. A sequential Monte Carlo model of the combined GB gas and electricity network

    International Nuclear Information System (INIS)

    Chaudry, Modassar; Wu, Jianzhong; Jenkins, Nick

    2013-01-01

    A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets

  4. Research on Large-Scale Road Network Partition and Route Search Method Combined with Traveler Preferences

    Directory of Open Access Journals (Sweden)

    De-Xin Yu

    2013-01-01

    Full Text Available Combined with improved Pallottino parallel algorithm, this paper proposes a large-scale route search method, which considers travelers’ route choice preferences. And urban road network is decomposed into multilayers effectively. Utilizing generalized travel time as road impedance function, the method builds a new multilayer and multitasking road network data storage structure with object-oriented class definition. Then, the proposed path search algorithm is verified by using the real road network of Guangzhou city as an example. By the sensitive experiments, we make a comparative analysis of the proposed path search method with the current advanced optimal path algorithms. The results demonstrate that the proposed method can increase the road network search efficiency by more than 16% under different search proportion requests, node numbers, and computing process numbers, respectively. Therefore, this method is a great breakthrough in the guidance field of urban road network.

  5. A combined Bodian-Nissl stain for improved network analysis in neuronal cell culture.

    Science.gov (United States)

    Hightower, M; Gross, G W

    1985-11-01

    Bodian and Nissl procedures were combined to stain dissociated mouse spinal cord cells cultured on coverslips. The Bodian technique stains fine neuronal processes in great detail as well as an intracellular fibrillar network concentrated around the nucleus and in proximal neurites. The Nissl stain clearly delimits neuronal cytoplasm in somata and in large dendrites. A combination of these techniques allows the simultaneous depiction of neuronal perikarya and all afferent and efferent processes. Costaining with little background staining by either procedure suggests high specificity for neurons. This procedure could be exploited for routine network analysis of cultured neurons.

  6. Modeling the future evolution of the virtual water trade network: A combination of network and gravity models

    Science.gov (United States)

    Sartori, Martina; Schiavo, Stefano; Fracasso, Andrea; Riccaboni, Massimo

    2017-12-01

    The paper investigates how the topological features of the virtual water (VW) network and the size of the associated VW flows are likely to change over time, under different socio-economic and climate scenarios. We combine two alternative models of network formation -a stochastic and a fitness model, used to describe the structure of VW flows- with a gravity model of trade to predict the intensity of each bilateral flow. This combined approach is superior to existing methodologies in its ability to replicate the observed features of VW trade. The insights from the models are used to forecast future VW flows in 2020 and 2050, under different climatic scenarios, and compare them with future water availability. Results suggest that the current trend of VW exports is not sustainable for all countries. Moreover, our approach highlights that some VW importers might be exposed to "imported water stress" as they rely heavily on imports from countries whose water use is unsustainable.

  7. FunCoup 4: new species, data, and visualization.

    Science.gov (United States)

    Ogris, Christoph; Guala, Dimitri; Sonnhammer, Erik L L

    2018-01-04

    This release of the FunCoup database (http://funcoup.sbc.su.se) is the fourth generation of one of the most comprehensive databases for genome-wide functional association networks. These functional associations are inferred via integrating various data types using a naive Bayesian algorithm and orthology based information transfer across different species. This approach provides high coverage of the included genomes as well as high quality of inferred interactions. In this update of FunCoup we introduce four new eukaryotic species: Schizosaccharomyces pombe, Plasmodium falciparum, Bos taurus, Oryza sativa and open the database to the prokaryotic domain by including networks for Escherichia coli and Bacillus subtilis. The latter allows us to also introduce a new class of functional association between genes - co-occurrence in the same operon. We also supplemented the existing classes of functional association: metabolic, signaling, complex and physical protein interaction with up-to-date information. In this release we switched to InParanoid v8 as the source of orthology and base for calculation of phylogenetic profiles. While populating all other evidence types with new data we introduce a new evidence type based on quantitative mass spectrometry data. Finally, the new JavaScript based network viewer provides the user an intuitive and responsive platform to further evaluate the results. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Disrupting Cocaine Trafficking Networks: Interdicting a Combined Social-Functional Network Model

    Science.gov (United States)

    2016-03-01

    BENEFITS OF STUDY ....................................14  E.  SOCIAL-FUNCTIONAL NETWORK DESCRIPTION .....................16  1.  A Representative...data to maintain appropriate classification levels) of cocaine produced each month by the Colombian sources to the U.S. homeland, netting the...Tactical interdiction-centric operational approaches have improved over the years due to previous studies and research, but these approaches rely upon one

  9. Material basis of Chinese herbal formulas explored by combining pharmacokinetics with network pharmacology.

    Directory of Open Access Journals (Sweden)

    Lixia Pei

    Full Text Available The clinical application of Traditional Chinese medicine (TCM, using several herbs in combination (called formulas, has a history of more than one thousand years. However, the bioactive compounds that account for their therapeutic effects remain unclear. We hypothesized that the material basis of a formula are those compounds with a high content in the decoction that are maintained at a certain level in the system circulation. Network pharmacology provides new methodological insights for complicated system studies. In this study, we propose combining pharmacokinetic (PK analysis with network pharmacology to explore the material basis of TCM formulas as exemplified by the Bushen Zhuanggu formula (BZ composed of Psoralea corylifolia L., Aconitum carmichaeli Debx., and Cnidium monnieri (L. Cuss. A sensitive and credible liquid chromatography tandem mass spectrometry (LC-MS/MS method was established for the simultaneous determination of 15 compounds present in the three herbs. The concentrations of these compounds in the BZ decoction and in rat plasma after oral BZ administration were determined. Up to 12 compounds were detected in the BZ decoction, but only 5 could be analyzed using PK parameters. Combined PK results, network pharmacology analysis revealed that 4 compounds might serve as the material basis for BZ. We concluded that a sensitive, reliable, and suitable LC-MS/MS method for both the composition and pharmacokinetic study of BZ has been established. The combination of PK with network pharmacology might be a potent method for exploring the material basis of TCM formulas.

  10. Synergistic target combination prediction from curated signaling networks: Machine learning meets systems biology and pharmacology.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Tucker-Kellogg, Lisa

    2017-10-01

    Given a signaling network, the target combination prediction problem aims to predict efficacious and safe target combinations for combination therapy. State-of-the-art in silico methods use Monte Carlo simulated annealing (mcsa) to modify a candidate solution stochastically, and use the Metropolis criterion to accept or reject the proposed modifications. However, such stochastic modifications ignore the impact of the choice of targets and their activities on the combination's therapeutic effect and off-target effects, which directly affect the solution quality. In this paper, we present mascot, a method that addresses this limitation by leveraging two additional heuristic criteria to minimize off-target effects and achieve synergy for candidate modification. Specifically, off-target effects measure the unintended response of a signaling network to the target combination and is often associated with toxicity. Synergy occurs when a pair of targets exerts effects that are greater than the sum of their individual effects, and is generally a beneficial strategy for maximizing effect while minimizing toxicity. mascot leverages on a machine learning-based target prioritization method which prioritizes potential targets in a given disease-associated network to select more effective targets (better therapeutic effect and/or lower off-target effects); and on Loewe additivity theory from pharmacology which assesses the non-additive effects in a combination drug treatment to select synergistic target activities. Our experimental study on two disease-related signaling networks demonstrates the superiority of mascot in comparison to existing approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Combined effect of storm movement and drainage network configuration on flood peaks

    Science.gov (United States)

    Seo, Yongwon; Son, Kwang Ik; Choi, Hyun Il

    2016-04-01

    This presentation reports the combined effect of storm movement and drainage network layout on resulting hydrographs and its implication to flood process and also flood mitigation. First, we investigate, in general terms, the effects of storm movement on the resulting flood peaks, and the underlying process controls. For this purpose, we utilize a broad theoretical framework that uses characteristic time and space scales associated with stationary rainstorms as well as moving rainstorms. For a stationary rainstorm the characteristic timescales that govern the peak response include two intrinsic timescales of a catchment and one extrinsic timescale of a rainstorm. On the other hand, for a moving rainstorm, two additional extrinsic scales are required; the storm travel time and storm size. We show that the relationship between the peak response and the timescales appropriate for a stationary rainstorm can be extended in a straightforward manner to describe the peak response for a moving rainstorm. For moving rainstorms, we show that the augmentation of peak response arises from both effect of overlaying the responses from subcatchments (resonance condition) and effect of increased responses from subcatchments due to increased duration (interdependence), which results in maximum peak response when the moving rainstorm is slower than the channel flow velocity. Second, we show the relation between channel network configurations and hydrograph sensitivity to storm kinematics. For this purpose, Gibbs' model is used to evaluate the network characteristics. The results show that the storm kinematics that produces the maximum peak discharge depends on the network configuration because the resonance condition changes with the network configuration. We show that an "efficient" network layout is more sensitive and results in higher increase in peak response compared to "inefficient" one. These results imply different flood potential risks for river networks depending on network

  12. Combined Simulated Annealing and Genetic Algorithm Approach to Bus Network Design

    Science.gov (United States)

    Liu, Li; Olszewski, Piotr; Goh, Pong-Chai

    A new method - combined simulated annealing (SA) and genetic algorithm (GA) approach is proposed to solve the problem of bus route design and frequency setting for a given road network with fixed bus stop locations and fixed travel demand. The method involves two steps: a set of candidate routes is generated first and then the best subset of these routes is selected by the combined SA and GA procedure. SA is the main process to search for a better solution to minimize the total system cost, comprising user and operator costs. GA is used as a sub-process to generate new solutions. Bus demand assignment on two alternative paths is performed at the solution evaluation stage. The method was implemented on four theoretical grid networks of different size and a benchmark network. Several GA operators (crossover and mutation) were utilized and tested for their effectiveness. The results show that the proposed method can efficiently converge to the optimal solution on a small network but computation time increases significantly with network size. The method can also be used for other transport operation management problems.

  13. Combining many interaction networks to predict gene function and analyze gene lists.

    Science.gov (United States)

    Mostafavi, Sara; Morris, Quaid

    2012-05-01

    In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming.

    Science.gov (United States)

    Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C

    2016-11-01

    Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. Interfaces entre funções executivas, linguagem e intencionalidade

    OpenAIRE

    Tonietto,Lauren; Wagner,Gabriela Peretti; Trentini,Clarissa Marceli; Sperb,Tania Mara; Parente,Maria Alice de Mattos Pimenta

    2011-01-01

    A relação entre linguagem e funções executivas, também conhecidas como funções cognitivas complexas, já foi estabelecida no passado por Luria e Vygotsky. Este artigo tem por objetivo revisar o conceito de funções executivas sob as perspectivas neuropsicológica e cognitiva. Alguns dos reconhecidos modelos sobre processamento das funções executivas são apresentados, assim como estudos recentes sobre funções executivas em crianças. O desenvolvimento das funções executivas é discutido sob o ponto...

  16. THERMODYNAMIC ANALYSIS AND SIMULATION OF A NEW COMBINED POWER AND REFRIGERATION CYCLE USING ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    Hossein Rezvantalab

    2011-01-01

    Full Text Available In this study, a new combined power and refrigeration cycle is proposed, which combines the Rankine and absorption refrigeration cycles. Using a binary ammonia-water mixture as the working fluid, this combined cycle produces both power and refrigeration output simultaneously by employing only one external heat source. In order to achieve the highest possible exergy efficiency, a secondary turbine is inserted to expand the hot weak solution leaving the boiler. Moreover, an artificial neural network (ANN is used to simulate the thermodynamic properties and the relationship between the input thermodynamic variables on the cycle performance. It is shown that turbine inlet pressure, as well as heat source and refrigeration temperatures have significant effects on the net power output, refrigeration output and exergy efficiency of the combined cycle. In addition, the results of ANN are in excellent agreement with the mathematical simulation and cover a wider range for evaluation of cycle performance.

  17. Towards Aiding Decision-Making in Social Networks by Using Sentiment and Stress Combined Analysis

    OpenAIRE

    Guillem Aguado; Vicente Julian; Ana Garcia-Fornes

    2018-01-01

    The present work is a study of the detection of negative emotional states that people have using social network sites (SNSs), and the effect that this negative state has on the repercussions of posted messages. We aim to discover in which grade a user having an affective state considered negative by an Analyzer can affect other users and generate bad repercussions. Those Analyzers that we propose are a Sentiment Analyzer, a Stress Analyzer and a novel combined Analyzer. We also want to discov...

  18. Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

    Science.gov (United States)

    Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

    2015-10-01

    An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

  19. Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

    Directory of Open Access Journals (Sweden)

    Da Xie

    2016-06-01

    Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.

  20. Risky Drinking Can Put a Chill on Your Summer Fun

    Science.gov (United States)

    ... on Your Summer Fun Print version Risky Drinking Can Put a Chill on Your Summer Fun Summer ... adults involve the use of alcohol. 1 Swimmers can get in over their heads. Alcohol impairs judgment ...

  1. Teaching for the Fun of It

    Science.gov (United States)

    Mitcham, Karen

    2009-01-01

    The purpose of having fun in the English language arts (ELA) classroom is twofold: (1) build community; and (2) alleviate the monotony, drudgery, and anxiety that reading, speaking, and writing often produce, especially in struggling students and any and all who are future members of Garrison Keillor's Lake Woebegone Professional Organization of…

  2. Putting the Fun Back into Fluency Instruction

    Science.gov (United States)

    Cahill, Mary Ann; Gregory, Anne E.

    2011-01-01

    Based on recent research in fluency instruction, the authors present a scenario in which a teacher focuses her fluency instruction on authentic fluency tasks based in performance. Beginning with establishing a student-friendly definition of fluency and culminating with student engagement in fun fluency activities, this article explores the…

  3. What Combinations of Contents is Driving Popularity in IPTV-based Social Networks?

    Science.gov (United States)

    Bhatt, Rajen

    IPTV-based Social Networks are gaining popularity with TV programs coming over IP connection and internet like applications available on home TV. One such application is rating TV programs over some predefined genres. In this paper, we suggest an approach for building a recommender system to be used by content distributors, publishers, and motion pictures producers-directors to decide on what combinations of contents may drive popularity or unpopularity. This may be used then for creating a proper mixture of media contents which can drive high popularity. This may also be used for the purpose of catering customized contents for group of users whose taste is similar and thus combinations of contents driving popularity for a certain group is also similar. We use a novel approach for this formulation utilizing fuzzy decision trees. Computational experiments performed over real-world program review database shows that the proposed approach is very efficient towards understanding of the content combinations.

  4. Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

    Science.gov (United States)

    Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

    2017-08-01

    The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P < 0.001. The areas under the ROC curve (AUC) and 95 % CI of prediction set from Fisher discrimination analysis and BP neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

  5. ComboCoding: Combined intra-/inter-flow network coding for TCP over disruptive MANETs

    Directory of Open Access Journals (Sweden)

    Chien-Chia Chen

    2011-07-01

    Full Text Available TCP over wireless networks is challenging due to random losses and ACK interference. Although network coding schemes have been proposed to improve TCP robustness against extreme random losses, a critical problem still remains of DATA–ACK interference. To address this issue, we use inter-flow coding between DATA and ACK to reduce the number of transmissions among nodes. In addition, we also utilize a “pipeline” random linear coding scheme with adaptive redundancy to overcome high packet loss over unreliable links. The resulting coding scheme, ComboCoding, combines intra-flow and inter-flow coding to provide robust TCP transmission in disruptive wireless networks. The main contributions of our scheme are twofold; the efficient combination of random linear coding and XOR coding on bi-directional streams (DATA and ACK, and the novel redundancy control scheme that adapts to time-varying and space-varying link loss. The adaptive ComboCoding was tested on a variable hop string topology with unstable links and on a multipath MANET with dynamic topology. Simulation results show that TCP with ComboCoding delivers higher throughput than with other coding options in high loss and mobile scenarios, while introducing minimal overhead in normal operation.

  6. Height, fun and safety in the design of children's playground equipment.

    Science.gov (United States)

    Wakes, Sarah; Beukes, Amanda

    2012-01-01

    The study reported in this paper adopted a holistic design approach to investigate issues associated with height related playground injuries from a users' perspective. The main objective was to gain an understanding of the relationship between height and fun so as to establish practical guidelines for addressing the causes of height related injuries whilst maintaining the attributes of playground equipment that children find fun and challenging. Results show that, on the one hand, the risk of injury increases when height is coupled with the use of upper body strength and, on the other hand, that coordination is a greater source of fun and challenge than height for children. Accordingly, it is suggested that the level of risk of injury attached to children's playground equipment can be reduced when the use of lower body strength and coordination are combined with lower free fall heights.

  7. Combining Topological Hardware and Topological Software: Color-Code Quantum Computing with Topological Superconductor Networks

    Science.gov (United States)

    Litinski, Daniel; Kesselring, Markus S.; Eisert, Jens; von Oppen, Felix

    2017-07-01

    We present a scalable architecture for fault-tolerant topological quantum computation using networks of voltage-controlled Majorana Cooper pair boxes and topological color codes for error correction. Color codes have a set of transversal gates which coincides with the set of topologically protected gates in Majorana-based systems, namely, the Clifford gates. In this way, we establish color codes as providing a natural setting in which advantages offered by topological hardware can be combined with those arising from topological error-correcting software for full-fledged fault-tolerant quantum computing. We provide a complete description of our architecture, including the underlying physical ingredients. We start by showing that in topological superconductor networks, hexagonal cells can be employed to serve as physical qubits for universal quantum computation, and we present protocols for realizing topologically protected Clifford gates. These hexagonal-cell qubits allow for a direct implementation of open-boundary color codes with ancilla-free syndrome read-out and logical T gates via magic-state distillation. For concreteness, we describe how the necessary operations can be implemented using networks of Majorana Cooper pair boxes, and we give a feasibility estimate for error correction in this architecture. Our approach is motivated by nanowire-based networks of topological superconductors, but it could also be realized in alternative settings such as quantum-Hall-superconductor hybrids.

  8. Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2016-01-01

    Full Text Available In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among inducing factors may be dependency, independence, and conflicting. Dempster-Shafer theory and neural network are effective and efficient strategies to deal with these difficulties and challenges. In this paper, we study trust and distrust prediction based on the combination of Dempster-Shafer theory and neural network. We firstly analyze the inducing factors about trust and distrust, namely, homophily, status theory, and emotion tendency. Then, we quantify inducing factors of trust and distrust, take these features as evidences, and construct evidence prototype as input nodes of multilayer neural network. Finally, we propose a framework of predicting trust and distrust which uses multilayer neural network to model the implementing process of Dempster-Shafer theory in different hidden layers, aiming to overcome the disadvantage of Dempster-Shafer theory without optimization method. Experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework.

  9. Combining Topological Hardware and Topological Software: Color-Code Quantum Computing with Topological Superconductor Networks

    Directory of Open Access Journals (Sweden)

    Daniel Litinski

    2017-09-01

    Full Text Available We present a scalable architecture for fault-tolerant topological quantum computation using networks of voltage-controlled Majorana Cooper pair boxes and topological color codes for error correction. Color codes have a set of transversal gates which coincides with the set of topologically protected gates in Majorana-based systems, namely, the Clifford gates. In this way, we establish color codes as providing a natural setting in which advantages offered by topological hardware can be combined with those arising from topological error-correcting software for full-fledged fault-tolerant quantum computing. We provide a complete description of our architecture, including the underlying physical ingredients. We start by showing that in topological superconductor networks, hexagonal cells can be employed to serve as physical qubits for universal quantum computation, and we present protocols for realizing topologically protected Clifford gates. These hexagonal-cell qubits allow for a direct implementation of open-boundary color codes with ancilla-free syndrome read-out and logical T gates via magic-state distillation. For concreteness, we describe how the necessary operations can be implemented using networks of Majorana Cooper pair boxes, and we give a feasibility estimate for error correction in this architecture. Our approach is motivated by nanowire-based networks of topological superconductors, but it could also be realized in alternative settings such as quantum-Hall–superconductor hybrids.

  10. COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS

    Directory of Open Access Journals (Sweden)

    Marijana Zekić-Sušac

    2013-02-01

    Full Text Available Despite increased interest in the entrepreneurial intentions and career choices of young adults, reliable prediction models are yet to be developed. Two nonparametric methods were used in this paper to model entrepreneurial intentions: principal component analysis (PCA and artificial neural networks (ANNs. PCA was used to perform feature extraction in the first stage of modelling, while artificial neural networks were used to classify students according to their entrepreneurial intentions in the second stage. Four modelling strategies were tested in order to find the most efficient model. Dataset was collected in an international survey on entrepreneurship self-efficacy and identity. Variables describe students’ demographics, education, attitudes, social and cultural norms, self-efficacy and other characteristics. The research reveals benefits from the combination of the PCA and ANNs in modeling entrepreneurial intentions, and provides some ideas for further research.

  11. Combined principal component preprocessing and n-tuple neural networks for improved classification

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar; Linneberg, Christian

    2000-01-01

    We present a combined principal component analysis/neural network scheme for classification. The data used to illustrate the method consist of spectral fluorescence recordings from seven different production facilities, and the task is to relate an unknown sample to one of these seven factories....... The data are first preprocessed by performing an individual principal component analysis on each of the seven groups of data. The components found are then used for classifying the data, but instead of making a single multiclass classifier, we follow the ideas of turning a multiclass problem into a number...... of two-class problems. For each possible pair of classes we further apply a transformation to the calculated principal components in order to increase the separation between the classes. Finally we apply the so-called n-tuple neural network to the transformed data in order to give the classification...

  12. Combining network analysis with Cognitive Work Analysis: insights into social organisational and cooperation analysis.

    Science.gov (United States)

    Houghton, Robert J; Baber, Chris; Stanton, Neville A; Jenkins, Daniel P; Revell, Kirsten

    2015-01-01

    Cognitive Work Analysis (CWA) allows complex, sociotechnical systems to be explored in terms of their potential configurations. However, CWA does not explicitly analyse the manner in which person-to-person communication is performed in these configurations. Consequently, the combination of CWA with Social Network Analysis provides a means by which CWA output can be analysed to consider communication structure. The approach is illustrated through a case study of a military planning team. The case study shows how actor-to-actor and actor-to-function mapping can be analysed, in terms of centrality, to produce metrics of system structure under different operating conditions. In this paper, a technique for building social network diagrams from CWA is demonstrated.The approach allows analysts to appreciate the potential impact of organisational structure on a command system.

  13. Analysing collaboration among HIV agencies through combining network theory and relational coordination.

    Science.gov (United States)

    Khosla, Nidhi; Marsteller, Jill Ann; Hsu, Yea Jen; Elliott, David L

    2016-02-01

    Agencies with different foci (e.g. nutrition, social, medical, housing) serve people living with HIV (PLHIV). Serving needs of PLHIV comprehensively requires a high degree of coordination among agencies which often benefits from more frequent communication. We combined Social Network theory and Relational Coordination theory to study coordination among HIV agencies in Baltimore. Social Network theory implies that actors (e.g., HIV agencies) establish linkages amongst themselves in order to access resources (e.g., information). Relational Coordination theory suggests that high quality coordination among agencies or teams relies on the seven dimensions of frequency, timeliness and accuracy of communication, problem-solving communication, knowledge of agencies' work, mutual respect and shared goals. We collected data on frequency of contact from 57 agencies using a roster method. Response options were ordinal ranging from 'not at all' to 'daily'. We analyzed data using social network measures. Next, we selected agencies with which at least one-third of the sample reported monthly or more frequent interaction. This yielded 11 agencies whom we surveyed on seven relational coordination dimensions with questions scored on a Likert scale of 1-5. Network density, defined as the proportion of existing connections to all possible connections, was 20% when considering monthly or higher interaction. Relational coordination scores from individual agencies to others ranged between 1.17 and 5.00 (maximum possible score 5). The average scores for different dimensions across all agencies ranged between 3.30 and 4.00. Shared goals (4.00) and mutual respect (3.91) scores were highest, while scores such as knowledge of each other's work and problem-solving communication were relatively lower. Combining theoretically driven analyses in this manner offers an innovative way to provide a comprehensive picture of inter-agency coordination and the quality of exchange that underlies

  14. Enhanced three-dimensional stochastic adjustment for combined volcano geodetic networks

    Science.gov (United States)

    Del Potro, R.; Muller, C.

    2009-12-01

    Volcano geodesy is unquestionably a necessary technique in studies of physical volcanology and for eruption early warning systems. However, as every volcano geodesist knows, obtaining measurements of the required resolution using traditional campaigns and techniques is time consuming and requires a large manpower. Moreover, most volcano geodetic networks worldwide use a combination of data from traditional techniques; levelling, electronic distance measurements (EDM), triangulation and Global Navigation Satellite Systems (GNSS) but, in most cases, these data are surveyed, analysed and adjusted independently. This then leaves it to the authors’ criteria to decide which technique renders the most realistic results in each case. Herein we present a way of solving the problem of inter-methodology data integration in a cost-effective manner following a methodology were all the geodetic data of a redundant, combined network (e.g. surveyed by GNSS, levelling, distance, angular data, INSAR, extensometers, etc.) is adjusted stochastically within a single three-dimensional referential frame. The adjustment methodology is based on the least mean square method and links the data with its geometrical component providing combined, precise, three-dimensional, displacement vectors, relative to external reference points as well as stochastically-quantified, benchmark-specific, uncertainty ellipsoids. Three steps in the adjustment allow identifying, and hence dismissing, flagrant measurement errors (antenna height, atmospheric effects, etc.), checking the consistency of external reference points and a final adjustment of the data. Moreover, since the statistical indicators can be obtained from expected uncertainties in the measurements of the different geodetic techniques used (i.e. independent of the measured data), it is possible to run a priori simulations of a geodetic network in order to constrain its resolution, and reduce logistics, before the network is even built. In this

  15. Choice of implant combinations in total hip replacement: systematic review and network meta-analysis.

    Science.gov (United States)

    López-López, José A; Humphriss, Rachel L; Beswick, Andrew D; Thom, Howard H Z; Hunt, Linda P; Burston, Amanda; Fawsitt, Christopher G; Hollingworth, William; Higgins, Julian P T; Welton, Nicky J; Blom, Ashley W; Marques, Elsa M R

    2017-11-02

    Objective  To compare the survival of different implant combinations for primary total hip replacement (THR). Design  Systematic review and network meta-analysis. Data sources  Medline, Embase, The Cochrane Library, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, and the EU Clinical Trials Register. Review methods  Published randomised controlled trials comparing different implant combinations. Implant combinations were defined by bearing surface materials (metal-on-polyethylene, ceramic-on-polyethylene, ceramic-on-ceramic, or metal-on-metal), head size (large ≥36 mm or small meta-analysis for revision. There was no evidence that the risk of revision surgery was reduced by other implant combinations compared with the reference implant combination. Although estimates are imprecise, metal-on-metal, small head, cemented implants (hazard ratio 4.4, 95% credible interval 1.6 to 16.6) and resurfacing (12.1, 2.1 to 120.3) increase the risk of revision at 0-2 years after primary THR compared with the reference implant combination. Similar results were observed for the 2-10 years period. 31 studies (2888 patients) were included in the analysis of Harris hip score. No implant combination had a better score than the reference implant combination. Conclusions  Newer implant combinations were not found to be better than the reference implant combination (metal-on-polyethylene (not highly cross linked), small head, cemented) in terms of risk of revision surgery or Harris hip score. Metal-on-metal, small head, cemented implants and resurfacing increased the risk of revision surgery compared with the reference implant combination. The results were consistent with observational evidence and were replicated in sensitivity analysis but were limited by poor reporting across studies. Systematic review registration  PROSPERO CRD42015019435. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence

  16. Adaptive Linear and Normalized Combination of Radial Basis Function Networks for Function Approximation and Regression

    Directory of Open Access Journals (Sweden)

    Yunfeng Wu

    2014-01-01

    Full Text Available This paper presents a novel adaptive linear and normalized combination (ALNC method that can be used to combine the component radial basis function networks (RBFNs to implement better function approximation and regression tasks. The optimization of the fusion weights is obtained by solving a constrained quadratic programming problem. According to the instantaneous errors generated by the component RBFNs, the ALNC is able to perform the selective ensemble of multiple leaners by adaptively adjusting the fusion weights from one instance to another. The results of the experiments on eight synthetic function approximation and six benchmark regression data sets show that the ALNC method can effectively help the ensemble system achieve a higher accuracy (measured in terms of mean-squared error and the better fidelity (characterized by normalized correlation coefficient of approximation, in relation to the popular simple average, weighted average, and the Bagging methods.

  17. Analysis and forecast of railway coal transportation volume based on BP neural network combined forecasting model

    Science.gov (United States)

    Xu, Yongbin; Xie, Haihong; Wu, Liuyi

    2018-05-01

    The share of coal transportation in the total railway freight volume is about 50%. As is widely acknowledged, coal industry is vulnerable to the economic situation and national policies. Coal transportation volume fluctuates significantly under the new economic normal. Grasp the overall development trend of railway coal transportation market, have important reference and guidance significance to the railway and coal industry decision-making. By analyzing the economic indicators and policy implications, this paper expounds the trend of the coal transportation volume, and further combines the economic indicators with the high correlation with the coal transportation volume with the traditional traffic prediction model to establish a combined forecasting model based on the back propagation neural network. The error of the prediction results is tested, which proves that the method has higher accuracy and has practical application.

  18. A função exponencial.

    OpenAIRE

    Emerson de Oliveira Dantas

    2014-01-01

    Este trabalho tem por motivação a Equação Funcional de Cauchy f(x + y) = f(x).f(y), característica da Função Exponencial. Para chegarmos a essa equação iniciaremos o nosso estudo pelas definições e demonstrações das Propriedades da Potência de Expoente Real, destacando o caso em que a Potência tem Expoente Irracional, além de fazermos uma proposta pedagógica sobre o ensino de Potenciação, Caracterização da Função Exponencial e Equação Funcional Linear de Cauchy. This work is motivated by t...

  19. Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

    Science.gov (United States)

    Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

    2018-04-01

    Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

  20. A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

    International Nuclear Information System (INIS)

    Neaimeh, Myriam; Wardle, Robin; Jenkins, Andrew M.; Yi, Jialiang; Hill, Graeme; Lyons, Padraig F.; Hübner, Yvonne; Blythe, Phil T.; Taylor, Phil C.

    2015-01-01

    Highlights: • Working with unique datasets of EV charging and smart meter load demand. • Distribution networks are not a homogenous group with more capabilities to accommodate EVs than previously suggested. • Spatial and temporal diversity of EV charging demand alleviate the impacts on networks. • An extensive recharging infrastructure could enable connection of additional EVs on constrained distribution networks. • Electric utilities could increase the network capability to accommodate EVs by investing in recharging infrastructure. - Abstract: This work uses a probabilistic method to combine two unique datasets of real world electric vehicle charging profiles and residential smart meter load demand. The data was used to study the impact of the uptake of Electric Vehicles (EVs) on electricity distribution networks. Two real networks representing an urban and rural area, and a generic network representative of a heavily loaded UK distribution network were used. The findings show that distribution networks are not a homogeneous group with a variation of capabilities to accommodate EVs and there is a greater capability than previous studies have suggested. Consideration of the spatial and temporal diversity of EV charging demand has been demonstrated to reduce the estimated impacts on the distribution networks. It is suggested that distribution network operators could collaborate with new market players, such as charging infrastructure operators, to support the roll out of an extensive charging infrastructure in a way that makes the network more robust; create more opportunities for demand side management; and reduce planning uncertainties associated with the stochastic nature of EV charging demand.

  1. The fun culture in seniors' online communities.

    Science.gov (United States)

    Nimrod, Galit

    2011-04-01

    Previous research found that "fun on line" is the most dominant content in seniors' online communities. The present study aimed to further explore the fun culture in these communities and to discover its unique qualities. The study applied an online ethnography (netnography) approach, utilizing a full year's data from 6 leading seniors' online communities. The final database included about 50,000 posts. The majority of posts were part of online social games, including cognitive, associative, and creative games. The main subjects in all contents were sex, gender differences, aging, grandparenting, politics, faith, and alcohol. Main participatory behaviors were selective timing, using expressive style, and personalization of the online character. Although most participants were "lurkers," the active participants nurtured community norms and relationships, as reflected in the written dialogues. In a reality of limited alternatives for digital games that meet older adults' needs and interests, seniors found an independent system to satisfy their need for play. Seniors' online communities provided a unique form of casual leisure, whose nature varied among different groups of participants. The fun culture seemed to offer participants many desired benefits, including meaningful play, liminality and communitas, opportunity to practice and demonstrate their abilities, and means for coping with aging. Therefore, it may have positive impact on seniors' well-being and successful aging.

  2. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Bach Phi Duong

    2018-04-01

    Full Text Available The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs. The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.

  3. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis.

    Science.gov (United States)

    Duong, Bach Phi; Kim, Jong-Myon

    2018-04-07

    The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.

  4. [Effect of microneedle combined with Lauromacrogol on skin capillary network: experimental study].

    Science.gov (United States)

    Xu, Sida; Wei, Qiang; Fan, Youfen; Chen, Shihai; Liu, Qingfeng; Yin, Guoqiang; Liao, Mingde; Sun, Yu

    2014-11-01

    To explore the effect of microneedle combined with Lauromacrogol on skin capillary network. 24 male Leghone (1.5-2.0 kg in weight) were randomly divided into three groups as group A (microneedle combined with Lauromacrogol), B (microneedle combined with physiological saline) , and C(control). The cockscombs were treated. The specimens were taken on the 7th, 14th, 21th , and 28th day postoperatively. HE staining, immunohistochemical staining and special staining were performed for study of the number of capillary and collagen I/III , as well as elastic fibers. The color of cockscombs in group A became lightening after treatment. The number of capillary decreased as showing by HE staining. The collagen I and III in group B was significantly different from that in group A and C (P microneedle combined with Lauromacrogol could effectively reduce the capillary in cockscomb without any tissue fibrosis. Microneedle can stimulate the proliferation of elastic fiber, so as to improve the skin ageing process.

  5. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis

    Science.gov (United States)

    Kim, Jong-Myon

    2018-01-01

    The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance. PMID:29642466

  6. Astronomy Fun with Mobile Devices

    Science.gov (United States)

    Pilachowski, Catherine A.; Morris, Frank

    2016-01-01

    Those mobile devices your students bring to class can do more that tweet and text. Engage your students with these web-based astronomy learning tools that allow students to manipulate astronomical data to learn important concepts. The tools are HTML5, CSS3, Javascript-based applications that provide access to the content on iPad and Android tablets. With "Three Color" students can combine monochrome astronomical images taken through different color filters or in different wavelength regions into a single color image. "Star Clusters" allows students to compare images of clusters with a pre-defined template of colors and sizes to compare clusters of different ages. An adaptation of Travis Rector's "NovaSearch" allows students to examine images of the central regions of the Andromeda Galaxy to find novae and to measure the time over which the nova fades away. New additions to our suite of applications allow students to estimate the surface temperatures of exoplanets and the probability of life elsewhere in the Universe. Further information and access to these web-based tools are available at www.astro.indiana.edu/ala/.

  7. Combined Ozone Retrieval From METOP Sensors Using META-Training Of Deep Neural Networks

    Science.gov (United States)

    Felder, Martin; Sehnke, Frank; Kaifel, Anton

    2013-12-01

    The newest installment of our well-proven Neural Net- work Ozone Retrieval System (NNORSY) combines the METOP sensors GOME-2 and IASI with cloud information from AVHRR. Through the use of advanced meta- learning techniques like automatic feature selection and automatic architecture search applied to a set of deep neural networks, having at least two or three hidden layers, we have been able to avoid many technical issues normally encountered during the construction of such a joint retrieval system. This has been made possible by harnessing the processing power of modern consumer graphics cards with high performance graphic processors (GPU), which decreases training times by about two orders of magnitude. The system was trained on data from 2009 and 2010, including target ozone profiles from ozone sondes, ACE- FTS and MLS-AURA. To make maximum use of tropospheric information in the spectra, the data were partitioned into several sets of different cloud fraction ranges with the GOME-2 FOV, on which specialized retrieval networks are being trained. For the final ozone retrieval processing the different specialized networks are combined. The resulting retrieval system is very stable and does not show any systematic dependence on solar zenith angle, scan angle or sensor degradation. We present several sensitivity studies with regard to cloud fraction and target sensor type, as well as the performance in several latitude bands and with respect to independent validation stations. A visual cross-comparison against high-resolution ozone profiles from the KNMI EUMETSAT Ozone SAF product has also been performed and shows some distinctive features which we will briefly discuss. Overall, we demonstrate that a complex retrieval system can now be constructed with a minimum of ma- chine learning knowledge, using automated algorithms for many design decisions previously requiring expert knowledge. Provided sufficient training data and computation power of GPUs is available, the

  8. FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

    Science.gov (United States)

    Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

    2018-02-09

    Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

  9. Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder.

    Science.gov (United States)

    Saad, Jacqueline F; Griffiths, Kristi R; Kohn, Michael R; Clarke, Simon; Williams, Leanne M; Korgaonkar, Mayuresh S

    2017-01-01

    Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization. We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I ( n  = 16) or as ADHD-C ( n  = 18) and 28 matched typically developing controls, aged 8-17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry. Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in "nodal degree"). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization. Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be

  10. A signal combining technique based on channel shortening for cooperative sensor networks

    KAUST Repository

    Hussain, Syed Imtiaz; Alouini, Mohamed-Slim; Hasna, Mazen Omar

    2010-01-01

    The cooperative relaying process needs proper coordination among the communicating and the relaying nodes. This coordination and the required capabilities may not be available in some wireless systems, e.g. wireless sensor networks where the nodes are equipped with very basic communication hardware. In this paper, we consider a scenario where the source node transmits its signal to the destination through multiple relays in an uncoordinated fashion. The destination can capture the multiple copies of the transmitted signal through a Rake receiver. We analyze a situation where the number of Rake fingers N is less than that of the relaying nodes L. In this case, the receiver can combine N strongest signals out of L. The remaining signals will be lost and act as interference to the desired signal components. To tackle this problem, we develop a novel signal combining technique based on channel shortening. This technique proposes a processing block before the Rake reception which compresses the energy of L signal components over N branches while keeping the noise level at its minimum. The proposed scheme saves the system resources and makes the received signal compatible to the available hardware. Simulation results show that it outperforms the selection combining scheme. ©2010 IEEE.

  11. Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data.

    Science.gov (United States)

    Mounce, S R; Shepherd, W; Sailor, G; Shucksmith, J; Saul, A J

    2014-01-01

    Combined sewer overflows (CSOs) represent a common feature in combined urban drainage systems and are used to discharge excess water to the environment during heavy storms. To better understand the performance of CSOs, the UK water industry has installed a large number of monitoring systems that provide data for these assets. This paper presents research into the prediction of the hydraulic performance of CSOs using artificial neural networks (ANN) as an alternative to hydraulic models. Previous work has explored using an ANN model for the prediction of chamber depth using time series for depth and rain gauge data. Rainfall intensity data that can be provided by rainfall radar devices can be used to improve on this approach. Results are presented using real data from a CSO for a catchment in the North of England, UK. An ANN model trained with the pseudo-inverse rule was shown to be capable of predicting CSO depth with less than 5% error for predictions more than 1 hour ahead for unseen data. Such predictive approaches are important to the future management of combined sewer systems.

  12. A signal combining technique based on channel shortening for cooperative sensor networks

    KAUST Repository

    Hussain, Syed Imtiaz

    2010-06-01

    The cooperative relaying process needs proper coordination among the communicating and the relaying nodes. This coordination and the required capabilities may not be available in some wireless systems, e.g. wireless sensor networks where the nodes are equipped with very basic communication hardware. In this paper, we consider a scenario where the source node transmits its signal to the destination through multiple relays in an uncoordinated fashion. The destination can capture the multiple copies of the transmitted signal through a Rake receiver. We analyze a situation where the number of Rake fingers N is less than that of the relaying nodes L. In this case, the receiver can combine N strongest signals out of L. The remaining signals will be lost and act as interference to the desired signal components. To tackle this problem, we develop a novel signal combining technique based on channel shortening. This technique proposes a processing block before the Rake reception which compresses the energy of L signal components over N branches while keeping the noise level at its minimum. The proposed scheme saves the system resources and makes the received signal compatible to the available hardware. Simulation results show that it outperforms the selection combining scheme. ©2010 IEEE.

  13. Equal gain combining for cooperative spectrum sensing in cognitive radio networks

    KAUST Repository

    Hamza, Doha R.

    2014-08-01

    Sensing with equal gain combining (SEGC), a novel cooperative spectrum sensing technique for cognitive radio networks, is proposed. Cognitive radios simultaneously transmit their sensing results to the fusion center (FC) over multipath fading reporting channels. The cognitive radios estimate the phases of the reporting channels and use those estimates for coherent combining of the sensing results at the FC. A global decision is made at the FC by comparing the received signal with a threshold. We obtain the global detection probabilities and secondary throughput exactly through a moment generating function approach. We verify our solution via system simulation and demonstrate that the Chernoff bound and central limit theory approximation are not tight. The cases of hard sensing and soft sensing are considered and we provide examples in which hard sensing is advantageous to soft sensing. We contrast the performance of SEGC with maximum ratio combining of the sensors\\' results and provide examples where the former is superior. Furthermore, we evaluate the performance of SEGC against existing orthogonal reporting techniques such as time division multiple access (TDMA). SEGC performance always dominates that of TDMA in terms of secondary throughput. We also study the impact of phase and synchronization errors and demonstrate the robustness of the SEGC technique against such imperfections. © 2002-2012 IEEE.

  14. Combined Model of Intrinsic and Extrinsic Variability for Computational Network Design with Application to Synthetic Biology

    Science.gov (United States)

    Toni, Tina; Tidor, Bruce

    2013-01-01

    Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady

  15. Combining neural networks and signed particles to simulate quantum systems more efficiently

    Science.gov (United States)

    Sellier, Jean Michel

    2018-04-01

    Recently a new formulation of quantum mechanics has been suggested which describes systems by means of ensembles of classical particles provided with a sign. This novel approach mainly consists of two steps: the computation of the Wigner kernel, a multi-dimensional function describing the effects of the potential over the system, and the field-less evolution of the particles which eventually create new signed particles in the process. Although this method has proved to be extremely advantageous in terms of computational resources - as a matter of fact it is able to simulate in a time-dependent fashion many-body systems on relatively small machines - the Wigner kernel can represent the bottleneck of simulations of certain systems. Moreover, storing the kernel can be another issue as the amount of memory needed is cursed by the dimensionality of the system. In this work, we introduce a new technique which drastically reduces the computation time and memory requirement to simulate time-dependent quantum systems which is based on the use of an appropriately tailored neural network combined with the signed particle formalism. In particular, the suggested neural network is able to compute efficiently and reliably the Wigner kernel without any training as its entire set of weights and biases is specified by analytical formulas. As a consequence, the amount of memory for quantum simulations radically drops since the kernel does not need to be stored anymore as it is now computed by the neural network itself, only on the cells of the (discretized) phase-space which are occupied by particles. As its is clearly shown in the final part of this paper, not only this novel approach drastically reduces the computational time, it also remains accurate. The author believes this work opens the way towards effective design of quantum devices, with incredible practical implications.

  16. A Novel approach for predicting monthly water demand by combining singular spectrum analysis with neural networks

    Science.gov (United States)

    Zubaidi, Salah L.; Dooley, Jayne; Alkhaddar, Rafid M.; Abdellatif, Mawada; Al-Bugharbee, Hussein; Ortega-Martorell, Sandra

    2018-06-01

    Valid and dependable water demand prediction is a major element of the effective and sustainable expansion of municipal water infrastructures. This study provides a novel approach to quantifying water demand through the assessment of climatic factors, using a combination of a pretreatment signal technique, a hybrid particle swarm optimisation algorithm and an artificial neural network (PSO-ANN). The Singular Spectrum Analysis (SSA) technique was adopted to decompose and reconstruct water consumption in relation to six weather variables, to create a seasonal and stochastic time series. The results revealed that SSA is a powerful technique, capable of decomposing the original time series into many independent components including trend, oscillatory behaviours and noise. In addition, the PSO-ANN algorithm was shown to be a reliable prediction model, outperforming the hybrid Backtracking Search Algorithm BSA-ANN in terms of fitness function (RMSE). The findings of this study also support the view that water demand is driven by climatological variables.

  17. A Neural Network Combined Inverse Controller for a Two-Rear-Wheel Independently Driven Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Duo Zhang

    2014-07-01

    Full Text Available Vehicle active safety control is attracting ever increasing attention in the attempt to improve the stability and the maneuverability of electric vehicles. In this paper, a neural network combined inverse (NNCI controller is proposed, incorporating the merits of left-inversion and right-inversion. As the left-inversion soft-sensor can estimate the sideslip angle, while the right-inversion is utilized to decouple control. Then, the proposed NNCI controller not only linearizes and decouples the original nonlinear system, but also directly obtains immeasurable state feedback in constructing the right-inversion. Hence, the proposed controller is very practical in engineering applications. The proposed system is co-simulated based on the vehicle simulation package CarSim in connection with Matlab/Simulink. The results verify the effectiveness of the proposed control strategy.

  18. Combining Quality of Service and Topology Control in Directional Hybrid Wireless Networks

    National Research Council Canada - National Science Library

    Erwin, Michael C

    2006-01-01

    .... This thesis establishes a foundation for the definition and consideration of the unique network characteristics and requirements introduced by this novel instance of the Network Design Problem (NDP...

  19. Combined Sector and Channel Hopping Schemes for Efficient Rendezvous in Directional Antenna Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    AbdulMajid M. Al-Mqdashi

    2017-01-01

    Full Text Available Rendezvous is a prerequisite and important process for secondary users (SUs to establish data communications in cognitive radio networks (CRNs. Recently, there has been a proliferation of different channel hopping- (CH- based schemes that can provide rendezvous without relying on any predetermined common control channel. However, the existing CH schemes were designed with omnidirectional antennas which can degrade their rendezvous performance when applied in CRNs that are highly crowded with primary users (PUs. In such networks, the large number of PUs may lead to the inexistence of any common available channel between neighboring SUs which result in a failure of their rendezvous process. In this paper, we consider the utilization of directional antennas in CRNs for tackling the issue. Firstly, we propose two coprimality-based sector hopping (SH schemes that can provide efficient pairwise sector rendezvous in directional antenna CRNs (DIR-CRNs. Then, we propose an efficient CH scheme that can be combined within the SH schemes for providing a simultaneous sector and channel rendezvous. The guaranteed rendezvous of our schemes are proven by deriving the theoretical upper bounds of their rendezvous delay metrics. Furthermore, extensive simulation comparisons with other related rendezvous schemes are conducted to illustrate the significant outperformance of our schemes.

  20. Uncertainty assessment in geodetic network adjustment by combining GUM and Monte-Carlo-simulations

    Science.gov (United States)

    Niemeier, Wolfgang; Tengen, Dieter

    2017-06-01

    In this article first ideas are presented to extend the classical concept of geodetic network adjustment by introducing a new method for uncertainty assessment as two-step analysis. In the first step the raw data and possible influencing factors are analyzed using uncertainty modeling according to GUM (Guidelines to the Expression of Uncertainty in Measurements). This approach is well established in metrology, but rarely adapted within Geodesy. The second step consists of Monte-Carlo-Simulations (MC-simulations) for the complete processing chain from raw input data and pre-processing to adjustment computations and quality assessment. To perform these simulations, possible realizations of raw data and the influencing factors are generated, using probability distributions for all variables and the established concept of pseudo-random number generators. Final result is a point cloud which represents the uncertainty of the estimated coordinates; a confidence region can be assigned to these point clouds, as well. This concept may replace the common concept of variance propagation and the quality assessment of adjustment parameters by using their covariance matrix. It allows a new way for uncertainty assessment in accordance with the GUM concept for uncertainty modelling and propagation. As practical example the local tie network in "Metsähovi Fundamental Station", Finland is used, where classical geodetic observations are combined with GNSS data.

  1. Conflict detection and resolution rely on a combination of common and distinct cognitive control networks.

    Science.gov (United States)

    Li, Qi; Yang, Guochun; Li, Zhenghan; Qi, Yanyan; Cole, Michael W; Liu, Xun

    2017-12-01

    Cognitive control can be activated by stimulus-stimulus (S-S) and stimulus-response (S-R) conflicts. However, whether cognitive control is domain-general or domain-specific remains unclear. To deepen the understanding of the functional organization of cognitive control networks, we conducted activation likelihood estimation (ALE) from 111 neuroimaging studies to examine brain activation in conflict-related tasks. We observed that fronto-parietal and cingulo-opercular networks were commonly engaged by S-S and S-R conflicts, showing a domain-general pattern. In addition, S-S conflicts specifically activated distinct brain regions to a greater degree. These regions were implicated in the processing of the semantic-relevant attribute, including the inferior frontal cortex (IFC), superior parietal cortex (SPC), superior occipital cortex (SOC), and right anterior cingulate cortex (ACC). By contrast, S-R conflicts specifically activated the left thalamus, middle frontal cortex (MFC), and right SPC, which were associated with detecting response conflict and orienting spatial attention. These findings suggest that conflict detection and resolution involve a combination of domain-general and domain-specific cognitive control mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Who runs public health? A mixed-methods study combining qualitative and network analyses.

    Science.gov (United States)

    Oliver, Kathryn; de Vocht, Frank; Money, Annemarie; Everett, Martin

    2013-09-01

    Persistent health inequalities encourage researchers to identify new ways of understanding the policy process. Informal relationships are implicated in finding evidence and making decisions for public health policy (PHP), but few studies use specialized methods to identify key actors in the policy process. We combined network and qualitative data to identify the most influential individuals in PHP in a UK conurbation and describe their strategies to influence policy. Network data were collected by asking for nominations of powerful and influential people in PHP (n = 152, response rate 80%), and 23 semi-structured interviews were analysed using a framework approach. The most influential PHP makers in this conurbation were mid-level managers in the National Health Service and local government, characterized by managerial skills: controlling policy processes through gate keeping key organizations, providing policy content and managing selected experts and executives to lead on policies. Public health professionals and academics are indirectly connected to policy via managers. The most powerful individuals in public health are managers, not usually considered targets for research. As we show, they are highly influential through all stages of the policy process. This study shows the importance of understanding the daily activities of influential policy individuals.

  3. Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming.

    Science.gov (United States)

    Adhikari, Shyam Prasad; Yang, Changju; Slot, Krzysztof; Kim, Hyongsuk

    2018-01-10

    This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into "trail" and "non-trail" categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented.

  4. Enhanced activation of motor execution networks using action observation combined with imagination of lower limb movements.

    Directory of Open Access Journals (Sweden)

    Michael Villiger

    Full Text Available The combination of first-person observation and motor imagery, i.e. first-person observation of limbs with online motor imagination, is commonly used in interactive 3D computer gaming and in some movie scenes. These scenarios are designed to induce a cognitive process in which a subject imagines himself/herself acting as the agent in the displayed movement situation. Despite the ubiquity of this type of interaction and its therapeutic potential, its relationship to passive observation and imitation during observation has not been directly studied using an interactive paradigm. In the present study we show activation resulting from observation, coupled with online imagination and with online imitation of a goal-directed lower limb movement using functional MRI (fMRI in a mixed block/event-related design. Healthy volunteers viewed a video (first-person perspective of a foot kicking a ball. They were instructed to observe-only the action (O, observe and simultaneously imagine performing the action (O-MI, or imitate the action (O-IMIT. We found that when O-MI was compared to O, activation was enhanced in the ventralpremotor cortex bilaterally, left inferior parietal lobule and left insula. The O-MI and O-IMIT conditions shared many activation foci in motor relevant areas as confirmed by conjunction analysis. These results show that (i combining observation with motor imagery (O-MI enhances activation compared to observation-only (O in the relevant foot motor network and in regions responsible for attention, for control of goal-directed movements and for the awareness of causing an action, and (ii it is possible to extensively activate the motor execution network using O-MI, even in the absence of overt movement. Our results may have implications for the development of novel virtual reality interactions for neurorehabilitation interventions and other applications involving training of motor tasks.

  5. Fun and software exploring pleasure, paradox and pain in computing

    CERN Document Server

    Goriunova, Olga

    2014-01-01

    Fun and Software offers the untold story of fun as constitutive of the culture and aesthetics of computing. Fun in computing is a mode of thinking, making and experiencing. It invokes and convolutes the question of rationalism and logical reason, addresses the sensibilities and experience of computation and attests to its creative drives. By exploring topics as diverse as the pleasure and pain of the programmer, geek wit, affects of play and coding as a bodily pursuit of the unique in recursive structures, Fun and Software helps construct a different point of entry to the understanding of soft

  6. Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods

    Directory of Open Access Journals (Sweden)

    Antonella Iuliano

    2018-06-01

    Full Text Available Breast cancer is one of the most common invasive tumors causing high mortality among women. It is characterized by high heterogeneity regarding its biological and clinical characteristics. Several high-throughput assays have been used to collect genome-wide information for many patients in large collaborative studies. This knowledge has improved our understanding of its biology and led to new methods of diagnosing and treating the disease. In particular, system biology has become a valid approach to obtain better insights into breast cancer biological mechanisms. A crucial component of current research lies in identifying novel biomarkers that can be predictive for breast cancer patient prognosis on the basis of the molecular signature of the tumor sample. However, the high dimension and low sample size of data greatly increase the difficulty of cancer survival analysis demanding for the development of ad-hoc statistical methods. In this work, we propose novel screening-network methods that predict patient survival outcome by screening key survival-related genes and we assess the capability of the proposed approaches using METABRIC dataset. In particular, we first identify a subset of genes by using variable screening techniques on gene expression data. Then, we perform Cox regression analysis by incorporating network information associated with the selected subset of genes. The novelty of this work consists in the improved prediction of survival responses due to the different types of screenings (i.e., a biomedical-driven, data-driven and a combination of the two before building the network-penalized model. Indeed, the combination of the two screening approaches allows us to use the available biological knowledge on breast cancer and complement it with additional information emerging from the data used for the analysis. Moreover, we also illustrate how to extend the proposed approaches to integrate an additional omic layer, such as copy number

  7. SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association.

    Directory of Open Access Journals (Sweden)

    Liang Cheng

    Full Text Available Measuring similarity between diseases plays an important role in disease-related molecular function research. Functional associations between disease-related genes and semantic associations between diseases are often used to identify pairs of similar diseases from different perspectives. Currently, it is still a challenge to exploit both of them to calculate disease similarity. Therefore, a new method (SemFunSim that integrates semantic and functional association is proposed to address the issue.SemFunSim is designed as follows. First of all, FunSim (Functional similarity is proposed to calculate disease similarity using disease-related gene sets in a weighted network of human gene function. Next, SemSim (Semantic Similarity is devised to calculate disease similarity using the relationship between two diseases from Disease Ontology. Finally, FunSim and SemSim are integrated to measure disease similarity.The high average AUC (area under the receiver operating characteristic curve (96.37% shows that SemFunSim achieves a high true positive rate and a low false positive rate. 79 of the top 100 pairs of similar diseases identified by SemFunSim are annotated in the Comparative Toxicogenomics Database (CTD as being targeted by the same therapeutic compounds, while other methods we compared could identify 35 or less such pairs among the top 100. Moreover, when using our method on diseases without annotated compounds in CTD, we could confirm many of our predicted candidate compounds from literature. This indicates that SemFunSim is an effective method for drug repositioning.

  8. Combining structure, governance and context : A configurational approach to network effectiveness

    NARCIS (Netherlands)

    Raab, J.; Mannak, R.S.; Cambré, B.

    2015-01-01

    This study explores the way in which network structure (network integration), network context (resource munificence and stability), and network governance mode relate to net -work effectiveness. The model by Provan and Milward (Provan, Keith G., and H. Brinton Milward. 1995. A preliminary theory of

  9. Towards Aiding Decision-Making in Social Networks by Using Sentiment and Stress Combined Analysis

    Directory of Open Access Journals (Sweden)

    Guillem Aguado

    2018-05-01

    Full Text Available The present work is a study of the detection of negative emotional states that people have using social network sites (SNSs, and the effect that this negative state has on the repercussions of posted messages. We aim to discover in which grade a user having an affective state considered negative by an Analyzer can affect other users and generate bad repercussions. Those Analyzers that we propose are a Sentiment Analyzer, a Stress Analyzer and a novel combined Analyzer. We also want to discover what Analyzer is more suitable to predict a bad future situation, and in what context. We designed a Multi-Agent System (MAS that uses different Analyzers to protect or advise users. This MAS uses the trained and tested Analyzers to predict future bad situations in social media, which could be triggered by the actions of a user that has an emotional state considered negative. We conducted an experimentation with different datasets of text messages from Twitter.com to examine the ability of the system to predict bad repercussions, by comparing the polarity, stress level or combined value classification of the messages that are replies to the ones of the messages that originated them.

  10. Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    M. Udin Harun Al Rasyid

    2014-12-01

    Full Text Available Wireless sensor network (WSN uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme. Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.

  11. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Directory of Open Access Journals (Sweden)

    Hazlee Azil Illias

    Full Text Available It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN and particle swarm optimisation (PSO techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  12. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Science.gov (United States)

    Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

    2015-01-01

    It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  13. Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

    Science.gov (United States)

    Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

    2016-04-01

    Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

  14. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

    Science.gov (United States)

    2015-01-01

    It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works. PMID:26103634

  15. Combined application of mixture experimental design and artificial neural networks in the solid dispersion development.

    Science.gov (United States)

    Medarević, Djordje P; Kleinebudde, Peter; Djuriš, Jelena; Djurić, Zorica; Ibrić, Svetlana

    2016-01-01

    This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q10) and 20 (Q20) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.

  16. KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks

    DEFF Research Database (Denmark)

    Baumbach, Jan; Alcaraz, Nicolas; Pauling, Josch K.

    We tackle the problem of de-novo pathway extraction. Given a biological network and a set of case-control studies, KeyPathwayMiner efficiently extracts and visualizes all maximal connected sub-networks that contain mainly genes that are dysregulated, e.g., differentially expressed, in most cases ...

  17. The Italian forest sites of FunDivEUROPE: a new FP7 project on the functional significance of forest biodiversity in Europe

    Directory of Open Access Journals (Sweden)

    Bussotti F

    2012-12-01

    Full Text Available The Italian forest sites of FunDivEUROPE: a new FP7 project on the functional significance of forest biodiversity in Europe. FunDivEUROPE is a new project aiming at a deeper understanding of the role of forest diversity on ecosystem functions and service provisioning for society. This project combines three scientific platforms: experimental, exploratory and inventory. The exploratory platform is based on the observation of a broad range of properties, traits and ecological processes on a network of ca. 240 natural forest sites representing a gradient of tree species diversity in six focal regions of Europe (Spain, Italy, Germany, Poland, Finland and Romania. The Italian sites are located on the hills of central and Southern Tuscany and represent the category “thermophilous deciduous forest”. Almost one year of fieldwork was needed to select and characterize 36 plots measuring 30 x 30 m. Selection was based on criteria concerning tree mixtures and richness, structural parameters and main environmental variables. The main features of these sites are synthetically presented in this paper together with a short description of the project structure and scope. The aim is also to enhance dissemination of the potential implications for a sustainable forest management in Italy.

  18. Exploring multiple feature combination strategies with a recurrent neural network architecture for off-line handwriting recognition

    Science.gov (United States)

    Mioulet, L.; Bideault, G.; Chatelain, C.; Paquet, T.; Brunessaux, S.

    2015-01-01

    The BLSTM-CTC is a novel recurrent neural network architecture that has outperformed previous state of the art algorithms in tasks such as speech recognition or handwriting recognition. It has the ability to process long term dependencies in temporal signals in order to label unsegmented data. This paper describes different ways of combining features using a BLSTM-CTC architecture. Not only do we explore the low level combination (feature space combination) but we also explore high level combination (decoding combination) and mid-level (internal system representation combination). The results are compared on the RIMES word database. Our results show that the low level combination works best, thanks to the powerful data modeling of the LSTM neurons.

  19. Halloween: Have Fun and Stay Safe and Healthy!

    Centers for Disease Control (CDC) Podcasts

    2010-10-25

    Halloween is a fun time for kids, but it's no fun if you get sick or hurt. In this podcast for kids, the Kidtastics offer some simple ways to stay safe and healthy on Halloween.  Created: 10/25/2010 by CDC Office of Women’s Health.   Date Released: 10/25/2010.

  20. Fun and Enjoyment in Physical Education: Young People's Attitudes

    Science.gov (United States)

    Dismore, Harriet; Bailey, Richard

    2011-01-01

    Fun and enjoyment are recurring themes in physical education literature, although there has been some debate concerning the distinction between the two concepts. Whereas enjoyment is generally regarded as helpful in fostering positive attitudes towards physical education, fun has not always been considered an appropriate outcome of physical…

  1. The what as well as the why of animal fun.

    Science.gov (United States)

    Byrne, Richard W

    2015-01-05

    Fun is functional: play is evolution's way of making sure animals acquire and perfect valuable skills in circumstances of relative safety. Yet precisely what animals find fun has seldom been examined for what it can potentially reveal about how they represent and think about the world. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Kick, Glide, Pole! Cross-Country Skiing Fun (Part II)

    Science.gov (United States)

    Duoos, Bridget A.

    2012-01-01

    Part I of Kick, Glide, Pole! Cross-Country Skiing Fun, which was published in last issue, discussed how to select cross-country ski equipment, dress for the activity and the biomechanics of the diagonal stride. Part II focuses on teaching the diagonal stride technique and begins with a progression of indoor activities. Incorporating this fun,…

  3. "Ten Things" to Enhance Learning and Fun in the Classroom

    Science.gov (United States)

    Mermelstein, Aaron David

    2016-01-01

    This Teaching Technique introduces a fun, versatile game that gets students thinking, talking, and working together in the English as a second language (ESL) or English as a foreign language (EFL) classroom. It is easy to prepare, and it is a fun and efficient way to enhance learning. The game can be adapted to almost any grade level or ESL/EFL…

  4. Premature ventricular contraction detection combining deep neural networks and rules inference.

    Science.gov (United States)

    Zhou, Fei-Yan; Jin, Lin-Peng; Dong, Jun

    2017-06-01

    Premature ventricular contraction (PVC), which is a common form of cardiac arrhythmia caused by ectopic heartbeat, can lead to life-threatening cardiac conditions. Computer-aided PVC detection is of considerable importance in medical centers or outpatient ECG rooms. In this paper, we proposed a new approach that combined deep neural networks and rules inference for PVC detection. The detection performance and generalization were studied using publicly available databases: the MIT-BIH arrhythmia database (MIT-BIH-AR) and the Chinese Cardiovascular Disease Database (CCDD). The PVC detection accuracy on the MIT-BIH-AR database was 99.41%, with a sensitivity and specificity of 97.59% and 99.54%, respectively, which were better than the results from other existing methods. To test the generalization capability, the detection performance was also evaluated on the CCDD. The effectiveness of the proposed method was confirmed by the accuracy (98.03%), sensitivity (96.42%) and specificity (98.06%) with the dataset over 140,000 ECG recordings of the CCDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. An OFDM Receiver with Frequency Domain Diversity Combined Impulsive Noise Canceller for Underwater Network

    Science.gov (United States)

    Saotome, Rie; Hai, Tran Minh; Matsuda, Yasuto; Suzuki, Taisaku; Wada, Tomohisa

    2015-01-01

    In order to explore marine natural resources using remote robotic sensor or to enable rapid information exchange between ROV (remotely operated vehicles), AUV (autonomous underwater vehicle), divers, and ships, ultrasonic underwater communication systems are used. However, if the communication system is applied to rich living creature marine environment such as shallow sea, it suffers from generated Impulsive Noise so-called Shrimp Noise, which is randomly generated in time domain and seriously degrades communication performance in underwater acoustic network. With the purpose of supporting high performance underwater communication, a robust digital communication method for Impulsive Noise environments is necessary. In this paper, we propose OFDM ultrasonic communication system with diversity receiver. The main feature of the receiver is a newly proposed Frequency Domain Diversity Combined Impulsive Noise Canceller. The OFDM receiver utilizes 20–28 KHz ultrasonic channel and subcarrier spacing of 46.875 Hz (MODE3) and 93.750 Hz (MODE2) OFDM modulations. In addition, the paper shows Impulsive Noise distribution data measured at a fishing port in Okinawa and at a barge in Shizuoka prefectures and then proposed diversity OFDM transceivers architecture and experimental results are described. By the proposed Impulsive Noise Canceller, frame bit error rate has been decreased by 20–30%. PMID:26351656

  6. An OFDM Receiver with Frequency Domain Diversity Combined Impulsive Noise Canceller for Underwater Network.

    Science.gov (United States)

    Saotome, Rie; Hai, Tran Minh; Matsuda, Yasuto; Suzuki, Taisaku; Wada, Tomohisa

    2015-01-01

    In order to explore marine natural resources using remote robotic sensor or to enable rapid information exchange between ROV (remotely operated vehicles), AUV (autonomous underwater vehicle), divers, and ships, ultrasonic underwater communication systems are used. However, if the communication system is applied to rich living creature marine environment such as shallow sea, it suffers from generated Impulsive Noise so-called Shrimp Noise, which is randomly generated in time domain and seriously degrades communication performance in underwater acoustic network. With the purpose of supporting high performance underwater communication, a robust digital communication method for Impulsive Noise environments is necessary. In this paper, we propose OFDM ultrasonic communication system with diversity receiver. The main feature of the receiver is a newly proposed Frequency Domain Diversity Combined Impulsive Noise Canceller. The OFDM receiver utilizes 20-28 KHz ultrasonic channel and subcarrier spacing of 46.875 Hz (MODE3) and 93.750 Hz (MODE2) OFDM modulations. In addition, the paper shows Impulsive Noise distribution data measured at a fishing port in Okinawa and at a barge in Shizuoka prefectures and then proposed diversity OFDM transceivers architecture and experimental results are described. By the proposed Impulsive Noise Canceller, frame bit error rate has been decreased by 20-30%.

  7. Assessment of erosion and sedimentation dynamic in a combined sewer network using online turbidity monitoring.

    Science.gov (United States)

    Bersinger, T; Le Hécho, I; Bareille, G; Pigot, T

    2015-01-01

    Eroded sewer sediments are a significant source of organic matter discharge by combined sewer overflows. Many authors have studied the erosion and sedimentation processes at the scale of a section of sewer pipe and over short time periods. The objective of this study was to assess these processes at the scale of an entire sewer network and over 1 month, to understand whether phenomena observed on a small scale of space and time are still valid on a larger scale. To achieve this objective the continuous monitoring of turbidity was used. First, the study of successive rain events allows observation of the reduction of the available sediment and highlights the widely different erosion resistance for the different sediment layers. Secondly, calculation of daily chemical oxygen demand (COD) fluxes during the entire month was performed showing that sediment storage in the sewer pipe after a rain period is important and stops after 5 days. Nevertheless, during rainfall events, the eroded fluxes are more important than the whole sewer sediment accumulated during a dry weather period. This means that the COD fluxes promoted by runoff are substantial. This work confirms, with online monitoring, most of the conclusions from other studies on a smaller scale.

  8. Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method

    Directory of Open Access Journals (Sweden)

    Xuejun Chen

    2014-01-01

    Full Text Available As one of the most promising renewable resources in electricity generation, wind energy is acknowledged for its significant environmental contributions and economic competitiveness. Because wind fluctuates with strong variation, it is quite difficult to describe the characteristics of wind or to estimate the power output that will be injected into the grid. In particular, short-term wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one of the most difficult problems to be solved. This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H weighted average smoothing method, ensemble empirical mode decomposition (EEMD algorithm, and nonlinear autoregressive (NAR neural networks. The chosen datasets are ten-minute wind speed observations, including twelve samples, and our simulation indicates that the proposed methods perform much better than the traditional ones when addressing short-term wind speed forecasting problems.

  9. An OFDM Receiver with Frequency Domain Diversity Combined Impulsive Noise Canceller for Underwater Network

    Directory of Open Access Journals (Sweden)

    Rie Saotome

    2015-01-01

    Full Text Available In order to explore marine natural resources using remote robotic sensor or to enable rapid information exchange between ROV (remotely operated vehicles, AUV (autonomous underwater vehicle, divers, and ships, ultrasonic underwater communication systems are used. However, if the communication system is applied to rich living creature marine environment such as shallow sea, it suffers from generated Impulsive Noise so-called Shrimp Noise, which is randomly generated in time domain and seriously degrades communication performance in underwater acoustic network. With the purpose of supporting high performance underwater communication, a robust digital communication method for Impulsive Noise environments is necessary. In this paper, we propose OFDM ultrasonic communication system with diversity receiver. The main feature of the receiver is a newly proposed Frequency Domain Diversity Combined Impulsive Noise Canceller. The OFDM receiver utilizes 20–28 KHz ultrasonic channel and subcarrier spacing of 46.875 Hz (MODE3 and 93.750 Hz (MODE2 OFDM modulations. In addition, the paper shows Impulsive Noise distribution data measured at a fishing port in Okinawa and at a barge in Shizuoka prefectures and then proposed diversity OFDM transceivers architecture and experimental results are described. By the proposed Impulsive Noise Canceller, frame bit error rate has been decreased by 20–30%.

  10. Artificial neural network combined with principal component analysis for resolution of complex pharmaceutical formulations.

    Science.gov (United States)

    Ioele, Giuseppina; De Luca, Michele; Dinç, Erdal; Oliverio, Filomena; Ragno, Gaetano

    2011-01-01

    A chemometric approach based on the combined use of the principal component analysis (PCA) and artificial neural network (ANN) was developed for the multicomponent determination of caffeine (CAF), mepyramine (MEP), phenylpropanolamine (PPA) and pheniramine (PNA) in their pharmaceutical preparations without any chemical separation. The predictive ability of the ANN method was compared with the classical linear regression method Partial Least Squares 2 (PLS2). The UV spectral data between 220 and 300 nm of a training set of sixteen quaternary mixtures were processed by PCA to reduce the dimensions of input data and eliminate the noise coming from instrumentation. Several spectral ranges and different numbers of principal components (PCs) were tested to find the PCA-ANN and PLS2 models reaching the best determination results. A two layer ANN, using the first four PCs, was used with log-sigmoid transfer function in first hidden layer and linear transfer function in output layer. Standard error of prediction (SEP) was adopted to assess the predictive accuracy of the models when subjected to external validation. PCA-ANN showed better prediction ability in the determination of PPA and PNA in synthetic samples with added excipients and pharmaceutical formulations. Since both components are characterized by low absorptivity, the better performance of PCA-ANN was ascribed to the ability in considering all non-linear information from noise or interfering excipients.

  11. Priority substances in combined sewer overflows: case study of the Paris sewer network.

    Science.gov (United States)

    Gasperi, J; Garnaud, S; Rocher, V; Moilleron, R

    2011-01-01

    This study was undertaken to supply data on both priority pollutant (PP) occurrence and concentrations in combined sewer overflows (CSOs). A single rain event was studied on 13 sites within the Paris sewer network. For each sample, a total of 66 substances, including metals, polycyclic aromatic hydrocarbons (PAHs), pesticides, organotins, volatile organic compounds, chlorobenzenes, phthalates and alkylphenols were analyzed. Of the 66 compounds analyzed in all, 40 PPs including 12 priority hazardous substances were detected in CSOs. As expected, most metals were present in all samples, reflecting their ubiquitous nature. Chlorobenzenes and most pesticides were never quantified above the limit of quantification, while the majority of the other organic pollutants, except DEHP (median concentration: 22 μg.l(-1)), were found to lie in the μg.l(-1) range. For the particular rain event studied, the pollutant loads discharged by CSOs were evaluated and then compared to pollutant loads conveyed by the Seine River. Under the hydraulic conditions considered and according to the estimations performed, this comparison suggests that CSOs are potentially significant local source of metals, PAHs and DEHP. Depending on the substance, the ratio between the CSO and Seine River loads varied from 0.5 to 26, underscoring the important local impact of CSOs at the scale of this storm for most pollutants.

  12. Economics made fun, and made fun of: How ‘Fun’ redefines the Domain and Identity of the Economics Profession

    NARCIS (Netherlands)

    Dekker, E.; Teule, P.

    2012-01-01

    This paper compares two aspects of the use of ‘fun’ within the economics profession. It analyzes the way in which a recently emerged genre of economics-made-fun uses fun and surprising insights to reach new audiences. And it also analyzes the way in which humor is used within and from outside the

  13. Having Fun and Accepting Challenges Are Natural Instincts: Jigsaw Puzzles to Challenge Students and Test Their Abilities While Having Fun!

    Science.gov (United States)

    Rodenbaugh, Hanna R.; Lujan, Heidi L.; Rodenbaugh, David W.; DiCarlo, Stephen E.

    2014-01-01

    Because jigsaw puzzles are fun, and challenging, students will endure and discover that persistence and grit are rewarded. Importantly, play and fun have a biological place just like sleep and dreams. Students also feel a sense of accomplishment when they have completed a puzzle. Importantly, the reward of mastering a challenge builds confidence…

  14. Voice Quality Estimation in Combined Radio-VoIP Networks for Dispatching Systems

    Directory of Open Access Journals (Sweden)

    Jiri Vodrazka

    2016-01-01

    Full Text Available The voice quality modelling assessment and planning field is deeply and widely theoretically and practically mastered for common voice communication systems, especially for the public fixed and mobile telephone networks including Next Generation Networks (NGN - internet protocol based networks. This article seeks to contribute voice quality modelling assessment and planning for dispatching communication systems based on Internet Protocol (IP and private radio networks. The network plan, correction in E-model calculation and default values for the model are presented and discussed.

  15. After 65 years, research is still fun.

    Science.gov (United States)

    Hansel, William

    2013-01-01

    In 1946, at the end of World War II, I entered graduate school at Cornell University, where I remained for 44 years. During that time, my laboratory produced more than 300 publications in the field of reproductive biology, including studies on nutrition and reproduction, the role of the hypothalamus in pituitary gonadotropin release, corpus luteum formation and function, hormone assays, and estrous cycle synchronization. At age seventy, I retired from Cornell and accepted the Gordon Cain Endowed Professorship at Louisiana State University, where I continued my work on the bovine corpus luteum and added research on the collection, maturation, in vitro fertilization, and culture of bovine oocytes. In 1994, I moved to the Pennington Biomedical Research Center and soon thereafter started the research that led to development of the lytic peptide-gonadotropin conjugates, which target and destroy cancer cell membranes. I am continuing my work on the development of targeted cancer cell drugs and, yes, research is still fun!

  16. Fun cube based brain gym cognitive function assessment system.

    Science.gov (United States)

    Zhang, Tao; Lin, Chung-Chih; Yu, Tsang-Chu; Sun, Jing; Hsu, Wen-Chuin; Wong, Alice May-Kuen

    2017-05-01

    The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment. Three kinds of experiments were performed to evaluate the developed FC-based BG cognitive function assessment system. The experimental results showed that the Pearson correlation coefficient between the system's evaluation outcomes and the traditional Montreal Cognitive Assessment scores was 0.83. The average Technology Acceptance Model 2 score was close to six for 31 elderly subjects. Most subjects considered that the brain games are interesting and the FC human-machine interface is easy to learn and operate. The control group and the cognitive impairment group had statistically significant difference with respect to the accuracy of and the time taken for the brain cognitive function assessment games, including Animal Naming, Color Search, Trail Making Test, Change Blindness, and Forward / Backward Digit Span. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Material discovery by combining stochastic surface walking global optimization with a neural network.

    Science.gov (United States)

    Huang, Si-Da; Shang, Cheng; Zhang, Xiao-Jie; Liu, Zhi-Pan

    2017-09-01

    While the underlying potential energy surface (PES) determines the structure and other properties of a material, it has been frustrating to predict new materials from theory even with the advent of supercomputing facilities. The accuracy of the PES and the efficiency of PES sampling are two major bottlenecks, not least because of the great complexity of the material PES. This work introduces a "Global-to-Global" approach for material discovery by combining for the first time a global optimization method with neural network (NN) techniques. The novel global optimization method, named the stochastic surface walking (SSW) method, is carried out massively in parallel for generating a global training data set, the fitting of which by the atom-centered NN produces a multi-dimensional global PES; the subsequent SSW exploration of large systems with the analytical NN PES can provide key information on the thermodynamics and kinetics stability of unknown phases identified from global PESs. We describe in detail the current implementation of the SSW-NN method with particular focuses on the size of the global data set and the simultaneous energy/force/stress NN training procedure. An important functional material, TiO 2 , is utilized as an example to demonstrate the automated global data set generation, the improved NN training procedure and the application in material discovery. Two new TiO 2 porous crystal structures are identified, which have similar thermodynamics stability to the common TiO 2 rutile phase and the kinetics stability for one of them is further proved from SSW pathway sampling. As a general tool for material simulation, the SSW-NN method provides an efficient and predictive platform for large-scale computational material screening.

  18. Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

    International Nuclear Information System (INIS)

    Wang, Xun-Heng; Li, Lihua

    2015-01-01

    Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

  19. Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xun-Heng, E-mail: xhwang@hdu.edu.cn [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China); School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096 (China); Li, Lihua [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China)

    2015-05-15

    Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

  20. Novel amphiphilic poly(dimethylsiloxane) based polyurethane networks tethered with carboxybetaine and their combined antibacterial and anti-adhesive property

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Jingxian; Fu, Yuchen; Zhang, Qinghua, E-mail: qhzhang@zju.edu.cn; Zhan, Xiaoli; Chen, Fengqiu

    2017-08-01

    Highlights: • An amphiphilic poly(dimethylsiloxane) (PDMS) based polyurethane (PU) network tethered with carboxybetaine is prepared. • The surface distribution of PDMS and zwitterionic segments produces an obvious amphiphilic heterogeneous surface. • This designed PDMS-based amphiphilic PU network exhibits combined antibacterial and anti-adhesive properties. - Abstract: The traditional nonfouling materials are powerless against bacterial cells attachment, while the hydrophobic bactericidal surfaces always suffer from nonspecific protein adsorption and dead bacterial cells accumulation. Here, amphiphilic polyurethane (PU) networks modified with poly(dimethylsiloxane) (PDMS) and cationic carboxybetaine diol through simple crosslinking reaction were developed, which had an antibacterial efficiency of 97.7%. Thereafter, the hydrolysis of carboxybetaine ester into zwitterionic groups brought about anti-adhesive properties against bacteria and proteins. The surface chemical composition and wettability performance of the PU network surfaces were investigated by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS) and contact angle analysis. The surface distribution of PDMS and zwitterionic segments produced an obvious amphiphilic heterogeneous surface, which was demonstrated by atomic force microscopy (AFM). Enzyme-linked immunosorbent assays (ELISA) were used to test the nonspecific protein adsorption behaviors. With the advantages of the transition from excellent bactericidal performance to anti-adhesion and the combination of fouling resistance and fouling release property, the designed PDMS-based amphiphilic PU network shows great application potential in biomedical devices and marine facilities.

  1. A new and accurate fault location algorithm for combined transmission lines using Adaptive Network-Based Fuzzy Inference System

    Energy Technology Data Exchange (ETDEWEB)

    Sadeh, Javad; Afradi, Hamid [Electrical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, P.O. Box: 91775-1111, Mashhad (Iran)

    2009-11-15

    This paper presents a new and accurate algorithm for locating faults in a combined overhead transmission line with underground power cable using Adaptive Network-Based Fuzzy Inference System (ANFIS). The proposed method uses 10 ANFIS networks and consists of 3 stages, including fault type classification, faulty section detection and exact fault location. In the first part, an ANFIS is used to determine the fault type, applying four inputs, i.e., fundamental component of three phase currents and zero sequence current. Another ANFIS network is used to detect the faulty section, whether the fault is on the overhead line or on the underground cable. Other eight ANFIS networks are utilized to pinpoint the faults (two for each fault type). Four inputs, i.e., the dc component of the current, fundamental frequency of the voltage and current and the angle between them, are used to train the neuro-fuzzy inference systems in order to accurately locate the faults on each part of the combined line. The proposed method is evaluated under different fault conditions such as different fault locations, different fault inception angles and different fault resistances. Simulation results confirm that the proposed method can be used as an efficient means for accurate fault location on the combined transmission lines. (author)

  2. Combining social and genetic networks to study HIV transmission in mixing risk groups

    NARCIS (Netherlands)

    Zarrabi, N.; Prosperi, M.C.F.; Belleman, R.G.; Di Giambenedetto, S.; Fabbiani, M.; De Luca, A.; Sloot, P.M.A.

    2013-01-01

    Reconstruction of HIV transmission networks is important for understanding and preventing the spread of the virus and drug resistant variants. Mixing risk groups is important in network analysis of HIV in order to assess the role of transmission between risk groups in the HIV epidemic. Most of the

  3. Combining Host-based and network-based intrusion detection system

    African Journals Online (AJOL)

    These attacks were simulated using hping. The proposed system is implemented in Java. The results show that the proposed system is able to detect attacks both from within (host-based) and outside sources (network-based). Key Words: Intrusion Detection System (IDS), Host-based, Network-based, Signature, Security log.

  4. Combining epidemiological and genetic networks signifies the importance of early treatment in HIV-1 transmission

    NARCIS (Netherlands)

    Zarrabi, N.; Prosperi, M.; Belleman, R.G.; Colafigli, M.; De Luca, A.; Sloot, P.M.A.

    2012-01-01

    Inferring disease transmission networks is important in epidemiology in order to understand and prevent the spread of infectious diseases. Reconstruction of the infection transmission networks requires insight into viral genome data as well as social interactions. For the HIV-1 epidemic, current

  5. Facilitating sustainability through smart network design in combination with virtual power plant operation

    NARCIS (Netherlands)

    El Bakari, K.; Kling, W.L.

    2010-01-01

    While smart grids are considered as an outcome to integrate a high penetration level of dispersed generation (DG) in the power system, most distribution networks are still passive controlled. To accelerate the transition towards smart grids network operators can take two important steps: 1.

  6. Smart grids : combination of 'Virtual Power Plant'-concept and 'smart network'-design

    NARCIS (Netherlands)

    El Bakari, K.; Kling, W.L.

    2010-01-01

    The concept of virtual power plant (VPP) offers a solution to control and manage higher level of dispersed generation in nowadays passive distribution network. Under certain conditions the VPP is able to displace power and energy which implies more control on the energy flow in the networks. To

  7. Neural networks and traditional time series methods: a synergistic combination in state economic forecasts.

    Science.gov (United States)

    Hansen, J V; Nelson, R D

    1997-01-01

    Ever since the initial planning for the 1997 Utah legislative session, neural-network forecasting techniques have provided valuable insights for analysts forecasting tax revenues. These revenue estimates are critically important since agency budgets, support for education, and improvements to infrastructure all depend on their accuracy. Underforecasting generates windfalls that concern taxpayers, whereas overforecasting produces budget shortfalls that cause inadequately funded commitments. The pattern finding ability of neural networks gives insightful and alternative views of the seasonal and cyclical components commonly found in economic time series data. Two applications of neural networks to revenue forecasting clearly demonstrate how these models complement traditional time series techniques. In the first, preoccupation with a potential downturn in the economy distracts analysis based on traditional time series methods so that it overlooks an emerging new phenomenon in the data. In this case, neural networks identify the new pattern that then allows modification of the time series models and finally gives more accurate forecasts. In the second application, data structure found by traditional statistical tools allows analysts to provide neural networks with important information that the networks then use to create more accurate models. In summary, for the Utah revenue outlook, the insights that result from a portfolio of forecasts that includes neural networks exceeds the understanding generated from strictly statistical forecasting techniques. In this case, the synergy clearly results in the whole of the portfolio of forecasts being more accurate than the sum of the individual parts.

  8. CTF: Computer security competitions for learning and fun

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    CTF hacking competitions condense practical security knowledge in short and measurable challenges, in short: education, fun, prizes and fame! This talk is an introduction to these type of competitions from a player perspective over the years.

  9. FUN-L: gene prioritization for RNAi screens.

    Science.gov (United States)

    Lees, Jonathan G; Hériché, Jean-Karim; Morilla, Ian; Fernández, José M; Adler, Priit; Krallinger, Martin; Vilo, Jaak; Valencia, Alfonso; Ellenberg, Jan; Ranea, Juan A; Orengo, Christine

    2015-06-15

    Most biological processes remain only partially characterized with many components still to be identified. Given that a whole genome can usually not be tested in a functional assay, identifying the genes most likely to be of interest is of critical importance to avoid wasting resources. Given a set of known functionally related genes and using a state-of-the-art approach to data integration and mining, our Functional Lists (FUN-L) method provides a ranked list of candidate genes for testing. Validation of predictions from FUN-L with independent RNAi screens confirms that FUN-L-produced lists are enriched in genes with the expected phenotypes. In this article, we describe a website front end to FUN-L. The website is freely available to use at http://funl.org © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

    DEFF Research Database (Denmark)

    Brorsson, C.; Hansen, Niclas Tue; Hansen, Kasper Lage

    2009-01-01

    genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC......To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1...... region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein...

  11. Identifying and ranking influential spreaders in complex networks by combining a local-degree sum and the clustering coefficient

    Science.gov (United States)

    Li, Mengtian; Zhang, Ruisheng; Hu, Rongjing; Yang, Fan; Yao, Yabing; Yuan, Yongna

    2018-03-01

    Identifying influential spreaders is a crucial problem that can help authorities to control the spreading process in complex networks. Based on the classical degree centrality (DC), several improved measures have been presented. However, these measures cannot rank spreaders accurately. In this paper, we first calculate the sum of the degrees of the nearest neighbors of a given node, and based on the calculated sum, a novel centrality named clustered local-degree (CLD) is proposed, which combines the sum and the clustering coefficients of nodes to rank spreaders. By assuming that the spreading process in networks follows the susceptible-infectious-recovered (SIR) model, we perform extensive simulations on a series of real networks to compare the performances between the CLD centrality and other six measures. The results show that the CLD centrality has a competitive performance in distinguishing the spreading ability of nodes, and exposes the best performance to identify influential spreaders accurately.

  12. Visualization and Analysis of a Cardio Vascular Diseaseand MUPP1-related Biological Network combining Text Mining and Data Warehouse Approaches

    Directory of Open Access Journals (Sweden)

    Sommer Björn

    2010-03-01

    Full Text Available Detailed investigation of socially important diseases with modern experimental methods has resulted in the generation of large volume of valuable data. However, analysis and interpretation of this data needs application of efficient computational techniques and systems biology approaches. In particular, the techniques allowing the reconstruction of associative networks of various biological objects and events can be useful. In this publication, the combination of different techniques to create such a network associated with an abstract cell environment is discussed in order to gain insights into the functional as well as spatial interrelationships. It is shown that experimentally gained knowledge enriched with data warehouse content and text mining data can be used for the reconstruction and localization of a cardiovascular disease developing network beginning with MUPP1/MPDZ (multi-PDZ domain protein.

  13. Combining Neural Networks with Existing Methods to Estimate 1 in 100-Year Flood Event Magnitudes

    Science.gov (United States)

    Newson, A.; See, L.

    2005-12-01

    Over the last fifteen years artificial neural networks (ANN) have been shown to be advantageous for the solution of many hydrological modelling problems. The use of ANNs for flood magnitude estimation in ungauged catchments, however, is a relatively new and under researched area. In this paper ANNs are used to make estimates of the magnitude of the 100-year flood event (Q100) for a number of ungauged catchments. The data used in this study were provided by the Centre for Ecology and Hydrology's Flood Estimation Handbook (FEH), which contains information on catchments across the UK. Sixteen catchment descriptors for 719 catchments were used to train an ANN, which was split into a training, validation and test data set. The goodness-of-fit statistics on the test data set indicated good model performance, with an r-squared value of 0.8 and a coefficient of efficiency of 79 percent. Data for twelve ungauged catchments were then put through the trained ANN to produce estimates of Q100. Two other accepted methodologies were also employed: the FEH statistical method and the FSR (Flood Studies Report) design storm technique, both of which are used to produce flood frequency estimates. The advantage of developing an ANN model is that it provides a third figure to aid a hydrologist in making an accurate estimate. For six of the twelve catchments, there was a relatively low spread between estimates. In these instances, an estimate of Q100 could be made with a fair degree of certainty. Of the remaining six catchments, three had areas greater than 1000km2, which means the FSR design storm estimate cannot be used. Armed with the ANN model and the FEH statistical method the hydrologist still has two possible estimates to consider. For these three catchments, the estimates were also fairly similar, providing additional confidence to the estimation. In summary, the findings of this study have shown that an accurate estimation of Q100 can be made using the catchment descriptors of

  14. Combining Volcano Monitoring Timeseries Analyses with Bayesian Belief Networks to Update Hazard Forecast Estimates

    Science.gov (United States)

    Odbert, Henry; Hincks, Thea; Aspinall, Willy

    2015-04-01

    Volcanic hazard assessments must combine information about the physical processes of hazardous phenomena with observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We show how our method

  15. [Rapid Identification of Epicarpium Citri Grandis via Infrared Spectroscopy and Fluorescence Spectrum Imaging Technology Combined with Neural Network].

    Science.gov (United States)

    Pan, Sha-sha; Huang, Fu-rong; Xiao, Chi; Xian, Rui-yi; Ma, Zhi-guo

    2015-10-01

    To explore rapid reliable methods for detection of Epicarpium citri grandis (ECG), the experiment using Fourier Transform Attenuated Total Reflection Infrared Spectroscopy (FTIR/ATR) and Fluorescence Spectrum Imaging Technology combined with Multilayer Perceptron (MLP) Neural Network pattern recognition, for the identification of ECG, and the two methods are compared. Infrared spectra and fluorescence spectral images of 118 samples, 81 ECG and 37 other kinds of ECG, are collected. According to the differences in tspectrum, the spectra data in the 550-1 800 cm(-1) wavenumber range and 400-720 nm wavelength are regarded as the study objects of discriminant analysis. Then principal component analysis (PCA) is applied to reduce the dimension of spectroscopic data of ECG and MLP Neural Network is used in combination to classify them. During the experiment were compared the effects of different methods of data preprocessing on the model: multiplicative scatter correction (MSC), standard normal variable correction (SNV), first-order derivative(FD), second-order derivative(SD) and Savitzky-Golay (SG). The results showed that: after the infrared spectra data via the Savitzky-Golay (SG) pretreatment through the MLP Neural Network with the hidden layer function as sigmoid, we can get the best discrimination of ECG, the correct percent of training set and testing set are both 100%. Using fluorescence spectral imaging technology, corrected by the multiple scattering (MSC) results in the pretreatment is the most ideal. After data preprocessing, the three layers of the MLP Neural Network of the hidden layer function as sigmoid function can get 100% correct percent of training set and 96.7% correct percent of testing set. It was shown that the FTIR/ATR and fluorescent spectral imaging technology combined with MLP Neural Network can be used for the identification study of ECG and has the advantages of rapid, reliable effect.

  16. [Wellbeing, team spirit and a fun run for women].

    Science.gov (United States)

    Gougeon, Brigitte

    2017-12-01

    The fun run La Parisienne, has been bringing together in Paris every September for the last 21 years, thousands of women running alongside each other to say no to breast cancer. Many caregivers also take part, in teams or with friends, like at the Odysséa fun run in which families can also participate. Charity sports events for the benefit of research which promote femininity, team spirit, sharing and wellbeing. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  17. Research on method of nuclear power plant operation fault diagnosis based on a combined artificial neural network

    International Nuclear Information System (INIS)

    Liu Feng; Yu Ren; Li Fengyu; Zhang Meng

    2007-01-01

    To solve the online real-time diagnosis problem of the nuclear power plant in operating condition, a method based on a combined artificial neural network is put forward in the paper. Its main principle is: using the BP neural network for the fast group diagnosis, and then using the RBF neural network for distinguishing and verifying the diagnostic result. The accuracy of the method is verified using the simulation values of the key parameters in normal status and malfunction status of a nuclear power plant. The results show that the method combining the advantages of the two neural networks can not only diagnose the learned faults in similar power level of the nuclear power plant quickly and accurately, but also can identify the faults in different power status, as well as the unlearned faults. The outputs of the diagnosis system are in form of the reliability of the faults, and are changing with the lasting of the operation time of the plant. This makes the diagnosis results be more acceptable to operators. (authors)

  18. Comparing Attentional Networks in fetal alcohol spectrum disorder and the inattentive and combined subtypes of attention deficit hyperactivity disorder.

    Science.gov (United States)

    Kooistra, Libbe; Crawford, Susan; Gibbard, Ben; Kaplan, Bonnie J; Fan, Jin

    2011-01-01

    The Attention Network Test (ANT) was used to examine alerting, orienting, and executive control in fetal alcohol spectrum disorder (FASD) versus attention deficit hyperactivity disorder (ADHD). Participants were 113 children aged 7 to 10 years (31 ADHD-Combined, 16 ADHD-Primarily Inattentive, 28 FASD, 38 controls). Incongruent flanker trials triggered slower responses in both the ADHD-Combined and the FASD groups. Abnormal conflict scores in these same two groups provided additional evidence for the presence of executive function deficits. The ADHD-Primarily Inattentive group was indistinguishable from the controls on all three ANT indices, which highlights the possibility that this group constitutes a pathologically distinct entity.

  19. A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors

    International Nuclear Information System (INIS)

    Liu, Xiuli; Moreno, Blanca; García, Ana Salomé

    2016-01-01

    A combined forecast of Grey forecasting method and neural network back propagation model, which is called Grey Neural Network and Input-Output Combined Forecasting Model (GNF-IO model), is proposed. A real case of energy consumption forecast is used to validate the effectiveness of the proposed model. The GNF-IO model predicts coal, crude oil, natural gas, renewable and nuclear primary energy consumption volumes by Spain's 36 sub-sectors from 2010 to 2015 according to three different GDP growth scenarios (optimistic, baseline and pessimistic). Model test shows that the proposed model has higher simulation and forecasting accuracy on energy consumption than Grey models separately and other combination methods. The forecasts indicate that the primary energies as coal, crude oil and natural gas will represent on average the 83.6% percent of the total of primary energy consumption, raising concerns about security of supply and energy cost and adding risk for some industrial production processes. Thus, Spanish industry must speed up its transition to an energy-efficiency economy, achieving a cost reduction and increase in the level of self-supply. - Highlights: • Forecasting System Using Grey Models combined with Input-Output Models is proposed. • Primary energy consumption in Spain is used to validate the model. • The grey-based combined model has good forecasting performance. • Natural gas will represent the majority of the total of primary energy consumption. • Concerns about security of supply, energy cost and industry competitiveness are raised.

  20. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    Science.gov (United States)

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Combined modal split and assignment model for the multimodal transportation network of the economic circle in China

    Directory of Open Access Journals (Sweden)

    Sh. Li

    2009-09-01

    Full Text Available Economic circles have been formed and developing in China. An economic circle consists of more than one closely adjoining central cities and their influence zones. It is always the major engine for the development of one country’s economy and even for the world economy. A combined modal split and assignment model with deterministic travel demand is proposed for modelling passengers’ choices of intercity bus and train which are two main competing modes in the multimodal transportation network of the economic circle. The generalized travel cost model of highway and railway are used incorporating travel time, ticket fare and passenger’s discomfort. On the highway network, the interactions of private vehicles and intercity buses are asymmetric. Thus, a variational inequality formulation is proposed to describe the combined model. The streamlined diagonalization algorithm is presented to solve the combined model. The multimodal transportation network based on Yangtze River Delta economic circle is presented to illustrate the proposed method. The results show the efficiency of the proposed model.

  2. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings

    Science.gov (United States)

    Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Stroh, Albrecht

    2015-01-01

    Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. PMID:26661247

  3. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings.

    Science.gov (United States)

    Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Faber, Cornelius; Stroh, Albrecht

    2016-11-01

    Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca 2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca 2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca 2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca 2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. © The Author(s) 2015.

  4. It's fun to transcribe with Fun30: A model for nucleosome dynamics during RNA polymerase II-mediated elongation.

    Science.gov (United States)

    Lee, Junwoo; Choi, Eun Shik; Lee, Daeyoup

    2018-01-01

    The ability of elongating RNA polymerase II (RNAPII) to regulate the nucleosome barrier is poorly understood because we do not know enough about the involved factors and we lack a conceptual framework to model this process. Our group recently identified the conserved Fun30/SMARCAD1 family chromatin-remodeling factor, Fun30 Fft3 , as being critical for relieving the nucleosome barrier during RNAPII-mediated elongation, and proposed a model illustrating how Fun30 Fft3 may contribute to nucleosome disassembly during RNAPII-mediated elongation. Here, we present a model that describes nucleosome dynamics during RNAPII-mediated elongation in mathematical terms and addresses the involvement of Fun30 Fft3 in this process.

  5. Healthy habits are no fun: How Dutch youth negotiate discourses about food, fit, fat, and fun.

    Science.gov (United States)

    van Amsterdam, Noortje; Knoppers, Annelies

    2018-03-01

    In this article, we use the notion of "biopedagogical practices" to explore how Dutch youth respond to health messages that focus on body weight. Previous studies suggest that such health messages encourage body dissatisfaction in youth. Few studies, however, focus on the local/cultural specificity of youth's responses to these biopedagogical practices. In this article, we address questions about the re-interpretation of and resistance to health messages that Dutch youth engage in and how these can be understood in their local context. The data were drawn from two previously conducted studies in which a total of 64 Dutch teenagers (aged 12-18 years) took part. We employed a variety of qualitative data collection methods and a feminist poststructuralist perspective to analyze how Dutch youth negotiate biopedagogical practices about health. The results show that our participants constructed health in terms of appearance and reproduced negative constructions regarding fat embodiment. Yet they also often circumvented "healthy" lifestyle behaviors prescribed by biopedagogies of health. They did so first by avoiding physical activities because they were afraid of displaying fat embodiment in the settings of sport and physical education where surveillance is omnipresent. Second, they disregarded advice about healthy eating by drawing on having fun as an alternative discursive resource. We argue that having fun is both part of youth culture and characteristic of the discourse about sociability ( gezelligheid) that is a central element of Dutch culture.

  6. A combined geostatistical-optimization model for the optimal design of a groundwater quality monitoring network

    Science.gov (United States)

    Kolosionis, Konstantinos; Papadopoulou, Maria P.

    2017-04-01

    Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.

  7. Is Congenital Amusia a Disconnection Syndrome? A Study Combining Tract- and Network-Based Analysis

    Directory of Open Access Journals (Sweden)

    Jieqiong Wang

    2017-09-01

    Full Text Available Previous studies on congenital amusia mainly focused on the impaired fronto-temporal pathway. It is possible that neural pathways of amusia patients on a larger scale are affected. In this study, we investigated changes in structural connections by applying both tract-based and network-based analysis to DTI data of 12 subjects with congenital amusia and 20 demographic-matched normal controls. TBSS (tract-based spatial statistics was used to detect microstructural changes. The results showed that amusics had higher diffusivity indices in the corpus callosum, the right inferior/superior longitudinal fasciculus, and the right inferior frontal-occipital fasciculus (IFOF. The axial diffusivity values of the right IFOF were negatively correlated with musical scores in the amusia group. Network-based analysis showed that the efficiency of the brain network was reduced in amusics. The impairments of WM tracts were also found to be correlated with reduced network efficiency in amusics. This suggests that impaired WM tracts may lead to the reduced network efficiency seen in amusics. Our findings suggest that congenital amusia is a disconnection syndrome.

  8. Is Congenital Amusia a Disconnection Syndrome? A Study Combining Tract- and Network-Based Analysis.

    Science.gov (United States)

    Wang, Jieqiong; Zhang, Caicai; Wan, Shibiao; Peng, Gang

    2017-01-01

    Previous studies on congenital amusia mainly focused on the impaired fronto-temporal pathway. It is possible that neural pathways of amusia patients on a larger scale are affected. In this study, we investigated changes in structural connections by applying both tract-based and network-based analysis to DTI data of 12 subjects with congenital amusia and 20 demographic-matched normal controls. TBSS (tract-based spatial statistics) was used to detect microstructural changes. The results showed that amusics had higher diffusivity indices in the corpus callosum, the right inferior/superior longitudinal fasciculus, and the right inferior frontal-occipital fasciculus (IFOF). The axial diffusivity values of the right IFOF were negatively correlated with musical scores in the amusia group. Network-based analysis showed that the efficiency of the brain network was reduced in amusics. The impairments of WM tracts were also found to be correlated with reduced network efficiency in amusics. This suggests that impaired WM tracts may lead to the reduced network efficiency seen in amusics. Our findings suggest that congenital amusia is a disconnection syndrome.

  9. Combining SDM-Based Circuit Switching with Packet Switching in a Router for On-Chip Networks

    Directory of Open Access Journals (Sweden)

    Angelo Kuti Lusala

    2012-01-01

    Full Text Available A Hybrid router architecture for Networks-on-Chip “NoC” is presented, it combines Spatial Division Multiplexing “SDM” based circuit switching and packet switching in order to efficiently and separately handle both streaming and best-effort traffic generated in real-time applications. Furthermore the SDM technique is combined with Time Division Multiplexing “TDM” technique in the circuit switching part in order to increase path diversity, thus improving throughput while sharing communication resources among multiple connections. Combining these two techniques allows mitigating the poor resource usage inherent to circuit switching. In this way Quality of Service “QoS” is easily provided for the streaming traffic through the circuit-switched sub-router while the packet-switched sub-router handles best-effort traffic. The proposed hybrid router architectures were synthesized, placed and routed on an FPGA. Results show that a practicable Network-on-Chip “NoC” can be built using the proposed router architectures. 7 × 7 mesh NoCs were simulated in SystemC. Simulation results show that the probability of establishing paths through the NoC increases with the number of sub-channels and has its highest value when combining SDM with TDM, thereby significantly reducing contention in the NoC.

  10. Combined effect of chemical and electrical synapses in Hindmarsh-Rose neural networks on synchronization and the rate of information.

    Science.gov (United States)

    Baptista, M S; Moukam Kakmeni, F M; Grebogi, C

    2010-09-01

    In this work we studied the combined action of chemical and electrical synapses in small networks of Hindmarsh-Rose (HR) neurons on the synchronous behavior and on the rate of information produced (per time unit) by the networks. We show that if the chemical synapse is excitatory, the larger the chemical synapse strength used the smaller the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find desynchronous behavior. Otherwise, if the chemical synapse is inhibitory, the larger the chemical synapse strength used the larger the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find synchronous behaviors. Finally, we show how to calculate semianalytically an upper bound for the rate of information produced per time unit (Kolmogorov-Sinai entropy) in larger networks. As an application, we show that this upper bound is linearly proportional to the number of neurons in a network whose neurons are highly connected.

  11. Combined IR imaging-neural network method for the estimation of internal temperature in cooked chicken meat

    Science.gov (United States)

    Ibarra, Juan G.; Tao, Yang; Xin, Hongwei

    2000-11-01

    A noninvasive method for the estimation of internal temperature in chicken meat immediately following cooking is proposed. The external temperature from IR images was correlated with measured internal temperature through a multilayer neural network. To provide inputs for the network, time series experiments were conducted to obtain simultaneous observations of internal and external temperatures immediately after cooking during the cooling process. An IR camera working at the spectral band of 3.4 to 5.0 micrometers registered external temperature distributions without the interference of close-to-oven environment, while conventional thermocouples registered internal temperatures. For an internal temperature at a given time, simultaneous and lagged external temperature observations were used as the input of the neural network. Based on practical and statistical considerations, a criterion is established to reduce the nodes in the neural network input. The combined method was able to estimate internal temperature for times between 0 and 540 s within a standard error of +/- 1.01 degree(s)C, and within an error of +/- 1.07 degree(s)C for short times after cooking (3 min), with two thermograms at times t and t+30s. The method has great potential for monitoring of doneness of chicken meat in conveyor belt type cooking and can be used as a platform for similar studies in other food products.

  12. NEpiC: a network-assisted algorithm for epigenetic studies using mean and variance combined signals.

    Science.gov (United States)

    Ruan, Peifeng; Shen, Jing; Santella, Regina M; Zhou, Shuigeng; Wang, Shuang

    2016-09-19

    DNA methylation plays an important role in many biological processes. Existing epigenome-wide association studies (EWAS) have successfully identified aberrantly methylated genes in many diseases and disorders with most studies focusing on analysing methylation sites one at a time. Incorporating prior biological information such as biological networks has been proven to be powerful in identifying disease-associated genes in both gene expression studies and genome-wide association studies (GWAS) but has been under studied in EWAS. Although recent studies have noticed that there are differences in methylation variation in different groups, only a few existing methods consider variance signals in DNA methylation studies. Here, we present a network-assisted algorithm, NEpiC, that combines both mean and variance signals in searching for differentially methylated sub-networks using the protein-protein interaction (PPI) network. In simulation studies, we demonstrate the power gain from using both the prior biological information and variance signals compared to using either of the two or neither information. Applications to several DNA methylation datasets from the Cancer Genome Atlas (TCGA) project and DNA methylation data on hepatocellular carcinoma (HCC) from the Columbia University Medical Center (CUMC) suggest that the proposed NEpiC algorithm identifies more cancer-related genes and generates better replication results. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

    DEFF Research Database (Denmark)

    Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

    2016-01-01

    Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...

  14. Combined centralised and distributed mechanism for utilisation of node association in broadband wireless network

    Science.gov (United States)

    Ulvan, A.; Ulvan, M.; Pranoto, H.

    2018-02-01

    Mobile broadband wireless access system has the stations that might be fixed, nomadic or mobile. Regarding the mobility, the node association procedure is critical for network entry as well as network re-entry during handover. The flexibility and utilisation of MAC protocols scheduling have an important role. The standard provides the Partition Scheme as the scheduling mechanism which separates the allocation of minislots for scheduling. However, minislots cannot be flexibly reserved for centralised and distributed scheduling. In this paper we analysed the scheduling mechanism to improve the utilisation of minislots allocation during the exchange of MAC massages. The centralised and distributed scheduling is implemented in some topology scenarios. The result shows the proposed mechanism has better performance for node association than partition scheme.

  15. Combining evolutionary game theory and network theory to analyze human cooperation patterns

    International Nuclear Information System (INIS)

    Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro; Catania, Emanuele; Guardo, Ermanno; Pagano, Salvatore

    2016-01-01

    Highlights: • We investigate the evolutionary dynamics of human cooperation in a social network. • We introduce the concepts of “Critical Mass”, centrality measure and homophily. • The emergence of cooperation is affected by the spatial choice of the “Critical Mass”. • Our findings show that homophily speeds up the convergence towards cooperation. • Centrality and “Critical Mass” spatial choice partially offset the impact of homophily. - Abstract: As natural systems continuously evolve, the human cooperation dilemma represents an increasingly more challenging question. Humans cooperate in natural and social systems, but how it happens and what are the mechanisms which rule the emergence of cooperation, represent an open and fascinating issue. In this work, we investigate the evolution of cooperation through the analysis of the evolutionary dynamics of behaviours within the social network, where nodes can choose to cooperate or defect following the classical social dilemmas represented by Prisoner’s Dilemma and Snowdrift games. To this aim, we introduce a sociological concept and statistical estimator, “Critical Mass”, to detect the minimum initial seed of cooperators able to trigger the diffusion process, and the centrality measure to select within the social network. Selecting different spatial configurations of the Critical Mass nodes, we highlight how the emergence of cooperation can be influenced by this spatial choice of the initial core in the network. Moreover, we target to shed light how the concept of homophily, a social shaping factor for which “birds of a feather flock together”, can affect the evolutionary process. Our findings show that homophily allows speeding up the diffusion process and make quicker the convergence towards human cooperation, while centrality measure and thus the Critical Mass selection, play a key role in the evolution showing how the spatial configurations can create some hidden patterns, partially

  16. Neural networks for combined control of capacitor banks and voltage regulators in distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Z.; Rizy, D.T.

    1996-02-01

    A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I{sup 2}R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks an d one nine tap line regulator to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

  17. An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation.

    Science.gov (United States)

    Hayati, Elyas; Majnounian, Baris; Abdi, Ehsan; Sessions, John; Makhdoum, Majid

    2013-02-01

    Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.

  18. Application of a Hybrid Method Combining Grey Model and Back Propagation Artificial Neural Networks to Forecast Hepatitis B in China

    Directory of Open Access Journals (Sweden)

    Ruijing Gan

    2015-01-01

    Full Text Available Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right. It is critical for early prevention and may contribute to health services management and syndrome surveillance. This study investigates the use of a hybrid algorithm combining grey model (GM and back propagation artificial neural networks (BP-ANN to forecast hepatitis B in China based on the yearly numbers of hepatitis B and to evaluate the method’s feasibility. The results showed that the proposal method has advantages over GM (1, 1 and GM (2, 1 in all the evaluation indexes.

  19. Application of a hybrid method combining grey model and back propagation artificial neural networks to forecast hepatitis B in china.

    Science.gov (United States)

    Gan, Ruijing; Chen, Xiaojun; Yan, Yu; Huang, Daizheng

    2015-01-01

    Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right. It is critical for early prevention and may contribute to health services management and syndrome surveillance. This study investigates the use of a hybrid algorithm combining grey model (GM) and back propagation artificial neural networks (BP-ANN) to forecast hepatitis B in China based on the yearly numbers of hepatitis B and to evaluate the method's feasibility. The results showed that the proposal method has advantages over GM (1, 1) and GM (2, 1) in all the evaluation indexes.

  20. Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

    Energy Technology Data Exchange (ETDEWEB)

    Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.; Ratterman, Joseph D.

    2018-01-30

    Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selected link to the adjacent compute node connected to the compute node through the selected link.

  1. THE EFFECT OF FUN ATHLETICS EXERCISES ON PSYCHOMOTOR DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Mustafa Güler

    2017-04-01

    Full Text Available The purpose of this research was to investigate the effect of fun athletics exercises on the psychomotor development. The research group consisted of 9 boys and 27 girls with a total of 36 students between 11-14 ages in Kocaeli. In the study, the fun athletics exercises (featured somersault, obstacles to jump, slip under the barrier, slalom, training ladder, double jump, medicine ball handling applied for 90 minutes a day and 3 days a week over 8 weeks. The data was analyzed with Wilcoxon Matched Pairs Test and significance level was determined as α=0.05. According to findings of this study significant differences were found between pre and post tests results. As a result this study showed that fun athletic exercises have a positive effect on 11-14 aged children’s psychomotor development.

  2. Design and Development of RunForFun Mobile Application

    Directory of Open Access Journals (Sweden)

    Anci Anthony

    2018-01-01

    Full Text Available Race run for 5 km or 10 km has been trending recently in many places in Indonesia, especially in Surabaya where there were at least 11 events of race run. The participant's number also increased significantly compared to years before. However, among several race run events, it was seen that some events tended to be replicative and monotone, while among the participants recently were identified the need for increasing the fun factor. RunForFun is a mobile application which designed for participants to reach new experience when participating in a race run event. The mobile application will run on Android OS. The development method of this mobile application would use Reverse Waterfall method. The development of this mobile application uses Ionic Framework which utilizes Cordova as its base to deploy to smartphone devices. Subsequently, RunForRun was tested on 10 participants, and the test shows a significant increase in the fun factor from run race participants.

  3. KELT-FUN and the discovery of KELT-18b

    Science.gov (United States)

    McLeod, Kim K.; Melton, Casey; Stassun, Keivan G.; KELT Collaboration

    2017-01-01

    The Kilodegree Extremely Little Telescope (KELT) project is a ground-based, wide-field, synoptic sky survey whose primary goal is to discover exoplanets around bright (8 FUN) of observatories to vet and characterize the systems by obtaining more precise light curves and radial-velocities. KELT-FUN now includes nearly 50 telescopes around the world and the photometric follow-up is carried out by a diverse set of partners at universities, small colleges, high schools, and private amateur facilities, often with the help of students. We describe KELT-FUN operations and announce the discovery of KELT-18b, a strongly-irradiated hot Jupiter orbiting a mid-F star.

  4. Towards a proper assignment of systemic risk: the combined roles of network topology and shock characteristics.

    Science.gov (United States)

    Loepfe, Lasse; Cabrales, Antonio; Sánchez, Angel

    2013-01-01

    The 2007-2008 financial crisis solidified the consensus among policymakers that a macro-prudential approach to regulation and supervision should be adopted. The currently preferred policy option is the regulation of capital requirements, with the main focus on combating procyclicality and on identifying the banks that have a high systemic importance, those that are "too big to fail". Here we argue that the concept of systemic risk should include the analysis of the system as a whole and we explore systematically the most important properties for policy purposes of networks topology on resistance to shocks. In a thorough study going from analytical models to empirical data, we show two sharp transitions from safe to risky regimes: 1) diversification becomes harmful with just a small fraction (~2%) of the shocks sampled from a fat tailed shock distributions and 2) when large shocks are present a critical link density exists where an effective giant cluster forms and most firms become vulnerable. This threshold depends on the network topology, especially on modularity. Firm size heterogeneity has important but diverse effects that are heavily dependent on shock characteristics. Similarly, degree heterogeneity increases vulnerability only when shocks are directed at the most connected firms. Furthermore, by studying the structure of the core of the transnational corporation network from real data, we show that its stability could be clearly increased by removing some of the links with highest centrality betweenness. Our results provide a novel insight and arguments for policy makers to focus surveillance on the connections between firms, in addition to capital requirements directed at the nodes.

  5. Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity.

    Science.gov (United States)

    Penrod, Nadia M; Greene, Casey S; Moore, Jason H

    2014-01-01

    Molecularly targeted drugs promise a safer and more effective treatment modality than conventional chemotherapy for cancer patients. However, tumors are dynamic systems that readily adapt to these agents activating alternative survival pathways as they evolve resistant phenotypes. Combination therapies can overcome resistance but finding the optimal combinations efficiently presents a formidable challenge. Here we introduce a new paradigm for the design of combination therapy treatment strategies that exploits the tumor adaptive process to identify context-dependent essential genes as druggable targets. We have developed a framework to mine high-throughput transcriptomic data, based on differential coexpression and Pareto optimization, to investigate drug-induced tumor adaptation. We use this approach to identify tumor-essential genes as druggable candidates. We apply our method to a set of ER(+) breast tumor samples, collected before (n = 58) and after (n = 60) neoadjuvant treatment with the aromatase inhibitor letrozole, to prioritize genes as targets for combination therapy with letrozole treatment. We validate letrozole-induced tumor adaptation through coexpression and pathway analyses in an independent data set (n = 18). We find pervasive differential coexpression between the untreated and letrozole-treated tumor samples as evidence of letrozole-induced tumor adaptation. Based on patterns of coexpression, we identify ten genes as potential candidates for combination therapy with letrozole including EPCAM, a letrozole-induced essential gene and a target to which drugs have already been developed as cancer therapeutics. Through replication, we validate six letrozole-induced coexpression relationships and confirm the epithelial-to-mesenchymal transition as a process that is upregulated in the residual tumor samples following letrozole treatment. To derive the greatest benefit from molecularly targeted drugs it is critical to design combination

  6. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  7. Combining a dispersal model with network theory to assess habitat connectivity.

    Science.gov (United States)

    Lookingbill, Todd R; Gardner, Robert H; Ferrari, Joseph R; Keller, Cherry E

    2010-03-01

    Assessing the potential for threatened species to persist and spread within fragmented landscapes requires the identification of core areas that can sustain resident populations and dispersal corridors that can link these core areas with isolated patches of remnant habitat. We developed a set of GIS tools, simulation methods, and network analysis procedures to assess potential landscape connectivity for the Delmarva fox squirrel (DFS; Sciurus niger cinereus), an endangered species inhabiting forested areas on the Delmarva Peninsula, USA. Information on the DFS's life history and dispersal characteristics, together with data on the composition and configuration of land cover on the peninsula, were used as input data for an individual-based model to simulate dispersal patterns of millions of squirrels. Simulation results were then assessed using methods from graph theory, which quantifies habitat attributes associated with local and global connectivity. Several bottlenecks to dispersal were identified that were not apparent from simple distance-based metrics, highlighting specific locations for landscape conservation, restoration, and/or squirrel translocations. Our approach links simulation models, network analysis, and available field data in an efficient and general manner, making these methods useful and appropriate for assessing the movement dynamics of threatened species within landscapes being altered by human and natural disturbances.

  8. A New Processing Method Combined with BP Neural Network for Francis Turbine Synthetic Characteristic Curve Research

    Directory of Open Access Journals (Sweden)

    Junyi Li

    2017-01-01

    Full Text Available A BP (backpropagation neural network method is employed to solve the problems existing in the synthetic characteristic curve processing of hydroturbine at present that most studies are only concerned with data in the high efficiency and large guide vane opening area, which can hardly meet the research requirements of transition process especially in large fluctuation situation. The principle of the proposed method is to convert the nonlinear characteristics of turbine to torque and flow characteristics, which can be used for real-time simulation directly based on neural network. Results show that obtained sample data can be extended successfully to cover working areas wider under different operation conditions. Another major contribution of this paper is the resampling technique proposed in the paper to overcome the limitation to sample period simulation. In addition, a detailed analysis for improvements of iteration convergence of the pressure loop is proposed, leading to a better iterative convergence during the head pressure calculation. Actual applications verify that methods proposed in this paper have better simulation results which are closer to the field and provide a new perspective for hydroturbine synthetic characteristic curve fitting and modeling.

  9. The development of artificial neural networks to predict virological response to combination HIV therapy

    NARCIS (Netherlands)

    Larder, Brendan; Wang, Dechao; Revell, Andrew; Montaner, Julio; Harrigan, Richard; de Wolf, Frank; Lange, Joep; Wegner, Scott; Ruiz, Lidia; Pérez-Elías, Maria Jésus; Emery, Sean; Gatell, Jose; D'Arminio Monforte, Antonella; Torti, Carlo; Zazzi, Maurizio; Lane, Clifford

    2007-01-01

    When used in combination, antiretroviral drugs are highly effective for suppressing HIV replication. Nevertheless, treatment failure commonly occurs and is generally associated with viral drug resistance. The choice of an alternative regimen may be guided by a drug-resistance test. However,

  10. Blind source extraction for a combined fixed and wireless sensor network

    NARCIS (Netherlands)

    Bloemendal, B.B.A.J.; Laar, van de J.; Sommen, P.C.W.

    2012-01-01

    The emergence of wireless microphones in everyday life creates opportunities to exploit spatial diversity when using fixed microphone arrays combined with these wireless microphones. Traditional array signal processing (ASP) techniques are not suitable for such a scenario since the locations of the

  11. Equal gain combining for cooperative spectrum sensing in cognitive radio networks

    KAUST Repository

    Hamza, Doha R.; Aï ssa, Sonia; Aniba, Ghassane

    2014-01-01

    are not tight. The cases of hard sensing and soft sensing are considered and we provide examples in which hard sensing is advantageous to soft sensing. We contrast the performance of SEGC with maximum ratio combining of the sensors' results and provide examples

  12. Combining wireless sensor networks and semantic middleware for an Internet of Things-based sportsman/woman monitoring application.

    Science.gov (United States)

    Rodríguez-Molina, Jesús; Martínez, José-Fernán; Castillejo, Pedro; López, Lourdes

    2013-01-31

    Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

  13. Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application

    Science.gov (United States)

    Rodríguez-Molina, Jesús; Martínez, José-Fernán; Castillejo, Pedro; López, Lourdes

    2013-01-01

    Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained. PMID:23385405

  14. Combination of Markov state models and kinetic networks for the analysis of molecular dynamics simulations of peptide folding.

    Science.gov (United States)

    Radford, Isolde H; Fersht, Alan R; Settanni, Giovanni

    2011-06-09

    Atomistic molecular dynamics simulations of the TZ1 beta-hairpin peptide have been carried out using an implicit model for the solvent. The trajectories have been analyzed using a Markov state model defined on the projections along two significant observables and a kinetic network approach. The Markov state model allowed for an unbiased identification of the metastable states of the system, and provided the basis for commitment probability calculations performed on the kinetic network. The kinetic network analysis served to extract the main transition state for folding of the peptide and to validate the results from the Markov state analysis. The combination of the two techniques allowed for a consistent and concise characterization of the dynamics of the peptide. The slowest relaxation process identified is the exchange between variably folded and denatured species, and the second slowest process is the exchange between two different subsets of the denatured state which could not be otherwise identified by simple inspection of the projected trajectory. The third slowest process is the exchange between a fully native and a partially folded intermediate state characterized by a native turn with a proximal backbone H-bond, and frayed side-chain packing and termini. The transition state for the main folding reaction is similar to the intermediate state, although a more native like side-chain packing is observed.

  15. Novel amphiphilic poly(dimethylsiloxane) based polyurethane networks tethered with carboxybetaine and their combined antibacterial and anti-adhesive property

    Science.gov (United States)

    Jiang, Jingxian; Fu, Yuchen; Zhang, Qinghua; Zhan, Xiaoli; Chen, Fengqiu

    2017-08-01

    The traditional nonfouling materials are powerless against bacterial cells attachment, while the hydrophobic bactericidal surfaces always suffer from nonspecific protein adsorption and dead bacterial cells accumulation. Here, amphiphilic polyurethane (PU) networks modified with poly(dimethylsiloxane) (PDMS) and cationic carboxybetaine diol through simple crosslinking reaction were developed, which had an antibacterial efficiency of 97.7%. Thereafter, the hydrolysis of carboxybetaine ester into zwitterionic groups brought about anti-adhesive properties against bacteria and proteins. The surface chemical composition and wettability performance of the PU network surfaces were investigated by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS) and contact angle analysis. The surface distribution of PDMS and zwitterionic segments produced an obvious amphiphilic heterogeneous surface, which was demonstrated by atomic force microscopy (AFM). Enzyme-linked immunosorbent assays (ELISA) were used to test the nonspecific protein adsorption behaviors. With the advantages of the transition from excellent bactericidal performance to anti-adhesion and the combination of fouling resistance and fouling release property, the designed PDMS-based amphiphilic PU network shows great application potential in biomedical devices and marine facilities.

  16. Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application

    Directory of Open Access Journals (Sweden)

    Lourdes López

    2013-01-01

    Full Text Available Wireless Sensor Networks (WSNs are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

  17. Development of a platform to combine sensor networks and home robots to improve fall detection in the home environment.

    Science.gov (United States)

    Della Toffola, Luca; Patel, Shyamal; Chen, Bor-rong; Ozsecen, Yalgin M; Puiatti, Alessandro; Bonato, Paolo

    2011-01-01

    Over the last decade, significant progress has been made in the development of wearable sensor systems for continuous health monitoring in the home and community settings. One of the main areas of application for these wearable sensor systems is in detecting emergency events such as falls. Wearable sensors like accelerometers are increasingly being used to monitor daily activities of individuals at a risk of falls, detect emergency events and send alerts to caregivers. However, such systems tend to have a high rate of false alarms, which leads to low compliance levels. Home robots can enable caregivers with the ability to quickly make an assessment and intervene if an emergency event is detected. This can provide an additional layer for detecting false positives, which can lead to improve compliance. In this paper, we present preliminary work on the development of a fall detection system based on a combination sensor networks and home robots. The sensor network architecture comprises of body worn sensors and ambient sensors distributed in the environment. We present the software architecture and conceptual design home robotic platform. We also perform preliminary characterization of the sensor network in terms of latencies and battery lifetime.

  18. Application of a hybrid method based on the combination of genetic algorithm and Hopfield neural network for burnable poison placement

    International Nuclear Information System (INIS)

    Khoshahval, F.; Fadaei, A.

    2012-01-01

    Highlights: ► The performance of GA, HNN and combination of them in BPP optimization in PWR core are adequate. ► It seems HNN + GA arrives to better final parameter value in comparison with the two other methods. ► The computation time for HNN + GA is higher than GA and HNN. Thus a trade-off is necessary. - Abstract: In the last decades genetic algorithm (GA) and Hopfield Neural Network (HNN) have attracted considerable attention for the solution of optimization problems. In this paper, a hybrid optimization method based on the combination of the GA and HNN is introduced and applied to the burnable poison placement (BPP) problem to increase the quality of the results. BPP in a nuclear reactor core is a combinatorial and complicated problem. Arrangement and the worth of the burnable poisons (BPs) has an impressive effect on the main control parameters of a nuclear reactor. Improper design and arrangement of the BPs can be dangerous with respect to the nuclear reactor safety. In this paper, increasing BP worth along with minimizing the radial power peaking are considered as objective functions. Three optimization algorithms, genetic algorithm, Hopfield neural network optimization and a hybrid optimization method, are applied to the BPP problem and their efficiencies are compared. The hybrid optimization method gives better result in finding a better BP arrangement.

  19. Application of 1 D Finite Element Method in Combination with Laminar Solution Method for Pipe Network Analysis

    Science.gov (United States)

    Dudar, O. I.; Dudar, E. S.

    2017-11-01

    The features of application of the 1D dimensional finite element method (FEM) in combination with the laminar solutions method (LSM) for the calculation of underground ventilating networks are considered. In this case the processes of heat and mass transfer change the properties of a fluid (binary vapour-air mix). Under the action of gravitational forces it leads to such phenomena as natural draft, local circulation, etc. The FEM relations considering the action of gravity, the mass conservation law, the dependence of vapour-air mix properties on the thermodynamic parameters are derived so that it allows one to model the mentioned phenomena. The analogy of the elastic and plastic rod deformation processes to the processes of laminar and turbulent flow in a pipe is described. Owing to this analogy, the guaranteed convergence of the elastic solutions method for the materials of plastic type means the guaranteed convergence of the LSM for any regime of a turbulent flow in a rough pipe. By means of numerical experiments the convergence rate of the FEM - LSM is investigated. This convergence rate appeared much higher than the convergence rate of the Cross - Andriyashev method. Data of other authors on the convergence rate comparison for the finite element method, the Newton method and the method of gradient are provided. These data allow one to conclude that the FEM in combination with the LSM is one of the most effective methods of calculation of hydraulic and ventilating networks. The FEM - LSM has been used for creation of the research application programme package “MineClimate” allowing to calculate the microclimate parameters in the underground ventilating networks.

  20. The combined geodetic network adjusted on the reference ellipsoid – a comparison of three functional models for GNSS observations

    Directory of Open Access Journals (Sweden)

    Kadaj Roman

    2016-12-01

    Full Text Available The adjustment problem of the so-called combined (hybrid, integrated network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients. While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional

  1. Growing adaptive machines combining development and learning in artificial neural networks

    CERN Document Server

    Bredeche, Nicolas; Doursat, René

    2014-01-01

    The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

  2. Design and Performance Investigation for the Optical Combinational Networks at High Data Rate

    Science.gov (United States)

    Tripathi, Devendra Kr.

    2017-05-01

    This article explores performance study for optical combinational designs based on nonlinear characteristics with semiconductor optical amplifier (SOA). Two configurations for optical half-adder with non-return-to-zero modulation pattern altogether with Mach-Zehnder modulator, interferometer at 50-Gbps data rate have been successfully realized. Accordingly, SUM and CARRY outputs have been concurrently executed and verified for their output waveforms. Numerical simulations for variation of data rate and key design parameters have been effectively executed outcome with optimum performance. Investigations depict overall good performance of the design in terms of the extinction factor. It also inferred that all-optical realization based on SOA is competent scheme, as it circumvents costly optoelectronic translation. This could be well supportive to erect larger complex optical combinational circuits.

  3. Combining affinity proteomics and network context to identify new phosphatase substrates and adapters in growth pathways.

    Directory of Open Access Journals (Sweden)

    Francesca eSacco

    2014-05-01

    Full Text Available Protein phosphorylation homoeostasis is tightly controlled and pathological conditions are caused by subtle alterations of the cell phosphorylation profile. Altered levels of kinase activities have already been associated to specific diseases. Less is known about the impact of phosphatases, the enzymes that down-regulate phosphorylation by removing the phosphate groups. This is partly due to our poor understanding of the phosphatase-substrate network. Much of phosphatase substrate specificity is not based on intrinsic enzyme specificity with the catalytic pocket recognizing the sequence/structure context of the phosphorylated residue. In addition many phosphatase catalytic subunits do not form a stable complex with their substrates. This makes the inference and validation of phosphatase substrates a non-trivial task. Here, we present a novel approach that builds on the observation that much of phosphatase substrate selection is based on the network of physical interactions linking the phosphatase to the substrate. We first used affinity proteomics coupled to quantitative mass spectrometry to saturate the interactome of eight phosphatases whose down regulations was shown to affect the activation of the RAS-PI#K pathway. By integrating information from functional siRNA with protein interaction information, we develop a strategy that aims at inferring phosphatase physiological substrates. Graph analysis is used to identify protein scaffolds that may link the catalytic subunits to their substrates. By this approach we rediscover several previously described phosphatase substrate interactions and characterize two new protein scaffolds that promote the dephosphorylation of PTPN11 and ERK by DUSP18 and DUSP26 respectively.

  4. A diversity compression and combining technique based on channel shortening for cooperative networks

    KAUST Repository

    Hussain, Syed Imtiaz

    2012-02-01

    The cooperative relaying process with multiple relays needs proper coordination among the communicating and the relaying nodes. This coordination and the required capabilities may not be available in some wireless systems where the nodes are equipped with very basic communication hardware. We consider a scenario where the source node transmits its signal to the destination through multiple relays in an uncoordinated fashion. The destination captures the multiple copies of the transmitted signal through a Rake receiver. We analyze a situation where the number of Rake fingers N is less than that of the relaying nodes L. In this case, the receiver can combine N strongest signals out of L. The remaining signals will be lost and act as interference to the desired signal components. To tackle this problem, we develop a novel signal combining technique based on channel shortening principles. This technique proposes a processing block before the Rake reception which compresses the energy of L signal components over N branches while keeping the noise level at its minimum. The proposed scheme saves the system resources and makes the received signal compatible to the available hardware. Simulation results show that it outperforms the selection combining scheme. © 2012 IEEE.

  5. Linearized FUN3D for Rapid Aeroelastic and Aeroservoelastic Design and Analysis, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall objective of this Phase I project is to develop a hybrid approach in FUN3D, referred herein to as the Linearized FUN3D, for rapid aeroelastic and...

  6. Linearized FUN3D for Rapid Aeroelastic and Aeroservoelastic Design and Analysis, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — In Phase I, a prototypical FUN3D-based ZONA Euler Unsteady Solver (FunZEUS) was developed to generate the Generalized Aerodynamic Forces (GAFs) due to structural...

  7. Serious Fun: Using Toys to Demonstrate Fluid Mechanics Principles

    Science.gov (United States)

    Saviz, Camilla M.; Shakerin, Said

    2014-01-01

    Many students have owned or seen fluids toys in which two immiscible fluids within a closed container can be tilted to generate waves. These types of inexpensive and readily available toys are fun to play with, but they are also useful for provoking student learning about fluid properties or complex fluid behavior, including drop formation and…

  8. TYCTWD Programs Strive to Make Science Educational and Fun | Poster

    Science.gov (United States)

    By Carolynne Keenan, Contributing Writer Joseph Barchi, Jr, Ph.D., calls teaching “the noblest and most important profession.” So it makes sense that Barchi, senior scientist and head of the Glycoconjugate and NMR Section, Chemical Biology Laboratory, Center for Cancer Research, NCI at Frederick, would encourage his lab to offer a fun, educational program at Take Your Child to

  9. Bike Skills Training in PE Is Fun, Keeps Kids Safe

    Science.gov (United States)

    Wallace, Judi Lawson; Sutton, Nancy P.

    2015-01-01

    Incorporating bike skills into the elementary- and middle-school physical education curriculum encourages students to be physically active in a fun way while also learning bike safety skills. Winston-Salem's (NC) Safe Routes to School program demonstrates how collaboration with the public schools' health and physical education program can…

  10. Learning can’t be fun, can it

    NARCIS (Netherlands)

    Veugen, J.I.L.; drs Lange, de M.; Siebenhandl, K.; Wagner, M.; Zauchner, S.

    2007-01-01

    Inspired by research by Carrie Heeter et al. and the MIT Games-to-Teach project, we set up a small-scale empirical study on two educational games on Art aimed at primary school children. We found that both boys and girls liked to play these games; that one game scored better on our “fun index” and

  11. The interventional effect of new drugs combined with the Stupp protocol on glioblastoma: A network meta-analysis.

    Science.gov (United States)

    Li, Mei; Song, Xiangqi; Zhu, Jun; Fu, Aijun; Li, Jianmin; Chen, Tong

    2017-08-01

    New therapeutic agents in combination with the standard Stupp protocol (a protocol about the temozolomide combined with radiotherapy treatment with glioblastoma was research by Stupp R in 2005) were assessed to evaluate whether they were superior to the Stupp protocol alone, to determine the optimum treatment regimen for patients with newly diagnosed glioblastoma. We implemented a search strategy to identify studies in the following databases: PubMed, Cochrane Library, EMBASE, CNKI, CBM, Wanfang, and VIP, and assessed the quality of extracted data from the trials included. Statistical software was used to perform network meta-analysis. The use of novel therapeutic agents in combination with the Stupp protocol were all shown to be superior than the Stupp protocol alone for the treatment of newly diagnosed glioblastoma, ranked as follows: cilengitide 2000mg/5/week, bevacizumab in combination with irinotecan, nimotuzumab, bevacizumab, cilengitide 2000mg/2/week, cytokine-induced killer cell immunotherapy, and the Stupp protocol. In terms of serious adverse effects, the intervention group showed a 29% increase in the incidence of adverse events compared with the control group (patients treated only with Stupp protocol) with a statistically significant difference (RR=1.29; 95%CI 1.17-1.43; P<0.001). The most common adverse events were thrombocytopenia, lymphopenia, neutropenia, pneumonia, nausea, and vomiting, none of which were significantly different between the groups except for neutropenia, pneumonia, and embolism. All intervention drugs evaluated in our study were superior to the Stupp protocol alone when used in combination with it. However, we could not conclusively confirm whether cilengitide 2000mg/5/week was the optimum regime, as only one trial using this protocol was included in our study. Copyright © 2017. Published by Elsevier B.V.

  12. Compression and Combining Based on Channel Shortening and Rank Reduction Technique for Cooperative Wireless Sensor Networks

    KAUST Repository

    Ahmed, Qasim Zeeshan

    2013-12-18

    This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of L sensors. As the destination has the capacity of processing only U out of these L signals, the strongest U signals are selected while the remaining (L?U) signals are suppressed. A preprocessing block similar to channel-shortening is proposed in this contribution. However, this preprocessing block employs a rank-reduction technique instead of channel-shortening. By employing this preprocessing, we are able to decrease the computational complexity of the system without affecting the bit error rate (BER) performance. From our simulations, it can be shown that these schemes outperform the channel-shortening schemes in terms of computational complexity. In addition, the proposed schemes have a superior BER performance as compared to channel-shortening schemes when sensors employ fixed gain amplification. However, for sensors which employ variable gain amplification, a tradeoff exists in terms of BER performance between the channel-shortening and these schemes. These schemes outperform channel-shortening scheme for lower signal-to-noise ratio.

  13. Combined expert system/neural networks method for process fault diagnosis

    Science.gov (United States)

    Reifman, Jaques; Wei, Thomas Y. C.

    1995-01-01

    A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach.

  14. Combined expert system/neural networks method for process fault diagnosis

    Science.gov (United States)

    Reifman, J.; Wei, T.Y.C.

    1995-08-15

    A two-level hierarchical approach for process fault diagnosis of an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach. 9 figs.

  15. Adaptive Steganalysis Based on Selection Region and Combined Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Donghui Hu

    2017-01-01

    Full Text Available Digital image steganalysis is the art of detecting the presence of information hiding in carrier images. When detecting recently developed adaptive image steganography methods, state-of-art steganalysis methods cannot achieve satisfactory detection accuracy, because the adaptive steganography methods can adaptively embed information into regions with rich textures via the guidance of distortion function and thus make the effective steganalysis features hard to be extracted. Inspired by the promising success which convolutional neural network (CNN has achieved in the fields of digital image analysis, increasing researchers are devoted to designing CNN based steganalysis methods. But as for detecting adaptive steganography methods, the results achieved by CNN based methods are still far from expected. In this paper, we propose a hybrid approach by designing a region selection method and a new CNN framework. In order to make the CNN focus on the regions with complex textures, we design a region selection method by finding a region with the maximal sum of the embedding probabilities. To evolve more diverse and effective steganalysis features, we design a new CNN framework consisting of three separate subnets with independent structure and configuration parameters and then merge and split the three subnets repeatedly. Experimental results indicate that our approach can lead to performance improvement in detecting adaptive steganography.

  16. 76 FR 77175 - New York Fun Factory Fireworks Display, Western Long Island Sound; Mamaroneck, NY

    Science.gov (United States)

    2011-12-12

    ...-AA00 New York Fun Factory Fireworks Display, Western Long Island Sound; Mamaroneck, NY AGENCY: Coast... in support of the New York Fun Factory Fireworks display. This action is necessary to provide for the... the Coast Guard to define regulatory safety zones. On May 10, 2012 New York Fun Factory Events is...

  17. Fun in the College Classroom: Examining Its Nature and Relationship with Student Engagement

    Science.gov (United States)

    Tews, Michael J.; Jackson, Kathy; Ramsay, Crystal; Michel, John W.

    2015-01-01

    Despite the popular belief that fun has a positive impact in learning contexts, empirical research on fun in the classroom has been limited. To extend research in this area, the goal of this study was to develop and validate a new scale to assess fun in the classroom and examine its relationship with student engagement. The multi-stage scale…

  18. Risk assessment of 170 kV GIS connected to combined cable/OHL network

    DEFF Research Database (Denmark)

    Bak, Claus Leth; Kessel, Jakob; Atlason, Vidir

    2009-01-01

    performance, compared to a system consisting solely of AIS connected through overhead lines. The main purpose is to investigate whether overvoltage protection is necessary at the GIS busbar. The analysis is conducted by implementing a simulation model in PSCAD/EMTDC. Simulations are conducted for both SF......This paper concerns different investigations of lightning simulation of a combined 170 kV overhead line/cable connected GIS. This is interesting due to the increasing amount of underground cables and GIS in the Danish transmission system. This creates a different system with respect to lightning...... and BFO. Overvoltages are evaluated for varying front times of the lightning surge, different soil resistivities at the surge arrester grounding in the overhead line/cable transition point and a varying length of the connection cable between the transformer and the GIS busbar with a SA implemented...

  19. Optimal Seamline Detection for Orthoimage Mosaicking by Combining Deep Convolutional Neural Network and Graph Cuts

    Directory of Open Access Journals (Sweden)

    Li Li

    2017-07-01

    Full Text Available When mosaicking orthoimages, especially in urban areas with various obvious ground objects like buildings, roads, cars or trees, the detection of optimal seamlines is one of the key technologies for creating seamless and pleasant image mosaics. In this paper, we propose a new approach to detect optimal seamlines for orthoimage mosaicking with the use of deep convolutional neural network (CNN and graph cuts. Deep CNNs have been widely used in many fields of computer vision and photogrammetry in recent years, and graph cuts is one of the most widely used energy optimization frameworks. We first propose a deep CNN for land cover semantic segmentation in overlap regions between two adjacent images. Then, the energy cost of each pixel in the overlap regions is defined based on the classification probabilities of belonging to each of the specified classes. To find the optimal seamlines globally, we fuse the CNN-classified energy costs of all pixels into the graph cuts energy minimization framework. The main advantage of our proposed method is that the pixel similarity energy costs between two images are defined using the classification results of the CNN based semantic segmentation instead of using the image informations of color, gradient or texture as traditional methods do. Another advantage of our proposed method is that the semantic informations are fully used to guide the process of optimal seamline detection, which is more reasonable than only using the hand designed features defined to represent the image differences. Finally, the experimental results on several groups of challenging orthoimages show that the proposed method is capable of finding high-quality seamlines among urban and non-urban orthoimages, and outperforms the state-of-the-art algorithms and the commercial software based on the visual comparison, statistical evaluation and quantitative evaluation based on the structural similarity (SSIM index.

  20. PRODIAG: Combined expert system/neural network for process fault diagnosis. Volume 1, Theory

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.

    1995-09-01

    The function of the PRODIAG code is to diagnose on-line the root cause of a thermal-hydraulic (T-H) system transient with trace back to the identification of the malfunctioning component using the T-H instrumentation signals exclusively. The code methodology is based on the Al techniques of automated reasoning/expert systems (ES) and artificial neural networks (ANN). The research and development objective is to develop a generic code methodology which would be plant- and T-H-system-independent. For the ES part the only plant or T-H system specific code requirements would be implemented through input only and at that only through a Piping and Instrumentation Diagram (PID) database. For the ANN part the only plant or T-H system specific code requirements would be through the ANN training data for normal component characteristics and the same PID database information. PRODIAG would, therefore, be generic and portable from T-H system to T-H system and from plant to plant without requiring any code-related modifications except for the PID database and the ANN training with the normal component characteristics. This would give PRODIAG the generic feature which numerical simulation plant codes such as TRAC or RELAP5 have. As the code is applied to different plants and different T-H systems, only the connectivity information, the operating conditions and the normal component characteristics are changed, and the changes are made entirely through input. Verification and validation of PRODIAG would, be T-H system independent and would be performed only ``once``.

  1. Combining advanced networked technology and pedagogical methods to improve collaborative distance learning.

    Science.gov (United States)

    Staccini, Pascal; Dufour, Jean-Charles; Raps, Hervé; Fieschi, Marius

    2005-01-01

    Making educational material be available on a network cannot be reduced to merely implementing hypermedia and interactive resources on a server. A pedagogical schema has to be defined to guide students for learning and to provide teachers with guidelines to prepare valuable and upgradeable resources. Components of a learning environment, as well as interactions between students and other roles such as author, tutor and manager, can be deduced from cognitive foundations of learning, such as the constructivist approach. Scripting the way a student will to navigate among information nodes and interact with tools to build his/her own knowledge can be a good way of deducing the features of the graphic interface related to the management of the objects. We defined a typology of pedagogical resources, their data model and their logic of use. We implemented a generic and web-based authoring and publishing platform (called J@LON for Join And Learn On the Net) within an object-oriented and open-source programming environment (called Zope) embedding a content management system (called Plone). Workflow features have been used to mark the progress of students and to trace the life cycle of resources shared by the teaching staff. The platform integrated advanced on line authoring features to create interactive exercises and support live courses diffusion. The platform engine has been generalized to the whole curriculum of medical studies in our faculty; it also supports an international master of risk management in health care and will be extent to all other continuous training diploma.

  2. Combining CFD simulations with blockoriented heatflow-network model for prediction of photovoltaic energy-production

    International Nuclear Information System (INIS)

    Haber, I E; Farkas, I

    2011-01-01

    The exterior factors which influencing the working circumstances of photovoltaic modules are the irradiation, the optical air layer (Air Mass - AM), the irradiation angle, the environmental temperature and the cooling effect of the wind. The efficiency of photovoltaic (PV) devices is inversely proportional to the cell temperature and therefore the mounting of the PV modules can have a big affect on the cooling, due to wind flow-around and naturally convection. The construction of the modules could be described by a heatflow-network model, and that can define the equation which determines the cells temperature. An equation like this can be solved as a block oriented model with hybrid-analogue simulator such as Matlab-Simulink. In view of the flow field and the heat transfer, witch was calculated numerically, the heat transfer coefficients can be determined. Five inflow rates were set up for both pitched and flat roof cases, to let the trend of the heat transfer coefficient know, while these functions can be used for the Matlab/Simulink model. To model the free convection flows, the Boussinesq-approximation were used, integrated into the Navier-Stokes equations and the energy equation. It has been found that under a constant solar heat gain, the air velocity around the modules and behind the pitched-roof mounted module is increasing, proportionately to the wind velocities, and as result the heat transfer coefficient increases linearly, and can be described by a function in both cases. To the block based model the meteorological parameters and the results of the CFD simulations as single functions were attached. The final aim was to make a model that could be used for planning photovoltaic systems, and define their accurate performance for better sizing of an array of modules.

  3. GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

    Directory of Open Access Journals (Sweden)

    Beiko Robert G

    2005-02-01

    Full Text Available Abstract Background The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence- and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results GANN (available at http://bioinformatics.org.au/gann is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

  4. A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity.

    Science.gov (United States)

    Frost, William N; Wang, Jean; Brandon, Christopher J

    2007-05-15

    Optical recording studies of invertebrate neural networks with voltage-sensitive dyes seldom employ conventional intracellular electrodes. This may in part be due to the traditional reliance on compound microscopes for such work. While such microscopes have high light-gathering power, they do not provide depth of field, making working with sharp electrodes difficult. Here we describe a hybrid microscope design, with switchable compound and stereo objectives, that eases the use of conventional intracellular electrodes in optical recording experiments. We use it, in combination with a voltage-sensitive dye and photodiode array, to identify neurons participating in the swim motor program of the marine mollusk Tritonia. This microscope design should be applicable to optical recording studies in many preparations.

  5. Study of Aided Diagnosis of Hepatic Carcinoma Based on Artificial Neural Network Combined with Tumor Marker Group

    Science.gov (United States)

    Tan, Shanjuan; Feng, Feifei; Wu, Yongjun; Wu, Yiming

    To develop a computer-aided diagnostic scheme by using an artificial neural network (ANN) combined with tumor markers for diagnosis of hepatic carcinoma (HCC) as a clinical assistant method. 140 serum samples (50 malignant, 40 benign and 50 normal) were analyzed for α-fetoprotein (AFP), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), sialic acid (SA) and calcium (Ca). The five tumor marker values were then used as ANN inputs data. The result of ANN was compared with that of discriminant analysis by receiver operating characteristic (ROC) curve (AUC) analysis. The diagnostic accuracy of ANN and discriminant analysis among all samples of the test group was 95.5% and 79.3%, respectively. Analysis of multiple tumor markers based on ANN may be a better choice than the traditional statistical methods for differentiating HCC from benign or normal.

  6. Impact of dam failure-induced flood on road network using combined remote sensing and geospatial approach

    Science.gov (United States)

    Foumelis, Michael

    2017-01-01

    The applicability of the normalized difference water index (NDWI) to the delineation of dam failure-induced floods is demonstrated for the case of the Sparmos dam (Larissa, Central Greece). The approach followed was based on the differentiation of NDWI maps to accurately define the extent of the inundated area over different time spans using multimission Earth observation optical data. Besides using Landsat data, for which the index was initially designed, higher spatial resolution data from Sentinel-2 mission were also successfully exploited. A geospatial analysis approach was then introduced to rapidly identify potentially affected segments of the road network. This allowed for further correlation to actual damages in the following damage assessment and remediation activities. The proposed combination of geographic information systems and remote sensing techniques can be easily implemented by local authorities and civil protection agencies for mapping and monitoring flood events.

  7. Blood hyperviscosity identification with reflective spectroscopy of tongue tip based on principal component analysis combining artificial neural network.

    Science.gov (United States)

    Liu, Ming; Zhao, Jing; Lu, XiaoZuo; Li, Gang; Wu, Taixia; Zhang, LiFu

    2018-05-10

    With spectral methods, noninvasive determination of blood hyperviscosity in vivo is very potential and meaningful in clinical diagnosis. In this study, 67 male subjects (41 health, and 26 hyperviscosity according to blood sample analysis results) participate. Reflectance spectra of subjects' tongue tips is measured, and a classification method bases on principal component analysis combined with artificial neural network model is built to identify hyperviscosity. Hold-out and Leave-one-out methods are used to avoid significant bias and lessen overfitting problem, which are widely accepted in the model validation. To measure the performance of the classification, sensitivity, specificity, accuracy and F-measure are calculated, respectively. The accuracies with 100 times Hold-out method and 67 times Leave-one-out method are 88.05% and 97.01%, respectively. Experimental results indicate that the built classification model has certain practical value and proves the feasibility of using spectroscopy to identify hyperviscosity by noninvasive determination.

  8. Physical risk factors identification based on body sensor network combined to videotaping.

    Science.gov (United States)

    Vignais, Nicolas; Bernard, Fabien; Touvenot, Gérard; Sagot, Jean-Claude

    2017-11-01

    The aim of this study was to perform an ergonomic analysis of a material handling task by combining a subtask video analysis and a RULA computation, implemented continuously through a motion capture system combining inertial sensors and electrogoniometers. Five workers participated to the experiment. Seven inertial measurement units, placed on the worker's upper body (pelvis, thorax, head, arms, forearms), were implemented through a biomechanical model of the upper body to continuously provide trunk, neck, shoulder and elbow joint angles. Wrist joint angles were derived from electrogoniometers synchronized with the inertial measurement system. Worker's activity was simultaneously recorded using video. During post-processing, joint angles were used as inputs to a computationally implemented ergonomic evaluation based on the RULA method. Consequently a RULA score was calculated at each time step to characterize the risk of exposure of the upper body (right and left sides). Local risk scores were also computed to identify the anatomical origin of the exposure. Moreover, the video-recorded work activity was time-studied in order to classify and quantify all subtasks involved into the task. Results showed that mean RULA scores were at high risk for all participants (6 and 6.2 for right and left sides respectively). A temporal analysis demonstrated that workers spent most part of the work time at a RULA score of 7 (right: 49.19 ± 35.27%; left: 55.5 ± 29.69%). Mean local scores revealed that most exposed joints during the task were elbows, lower arms, wrists and hands. Elbows and lower arms were indeed at a high level of risk during the total time of a work cycle (100% for right and left sides). Wrist and hands were also exposed to a risky level for much of the period of work (right: 82.13 ± 7.46%; left: 77.85 ± 12.46%). Concerning the subtask analysis, subtasks called 'snow thrower', 'opening the vacuum sealer', 'cleaning' and 'storing' have been identified as

  9. A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

    Directory of Open Access Journals (Sweden)

    Dexing Zhong

    2014-07-01

    Full Text Available The so-called Internet of Things (IoT has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC, is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE installed in the driver’s operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP through General Packet Radio Service (GPRS. Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.

  10. A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

    Science.gov (United States)

    Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

    2014-01-01

    The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things. PMID:25196106

  11. Distributed least-squares estimation of a remote chemical source via convex combination in wireless sensor networks.

    Science.gov (United States)

    Cao, Meng-Li; Meng, Qing-Hao; Zeng, Ming; Sun, Biao; Li, Wei; Ding, Cheng-Jun

    2014-06-27

    This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

  12. Assessment of the service performance of drainage system and transformation of pipeline network based on urban combined sewer system model.

    Science.gov (United States)

    Peng, Hai-Qin; Liu, Yan; Wang, Hong-Wu; Ma, Lu-Ming

    2015-10-01

    In recent years, due to global climate change and rapid urbanization, extreme weather events occur to the city at an increasing frequency. Waterlogging is common because of heavy rains. In this case, the urban drainage system can no longer meet the original design requirements, resulting in traffic jams and even paralysis and post a threat to urban safety. Therefore, it provides a necessary foundation for urban drainage planning and design to accurately assess the capacity of the drainage system and correctly simulate the transport effect of drainage network and the carrying capacity of drainage facilities. This study adopts InfoWorks Integrated Catchment Management (ICM) to present the two combined sewer drainage systems in Yangpu District, Shanghai (China). The model can assist the design of the drainage system. Model calibration is performed based on the historical rainfall events. The calibrated model is used for the assessment of the outlet drainage and pipe loads for the storm scenario currently existing or possibly occurring in the future. The study found that the simulation and analysis results of the drainage system model were reliable. They could fully reflect the service performance of the drainage system in the study area and provide decision-making support for regional flood control and transformation of pipeline network.

  13. Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Meng-Li Cao

    2014-06-01

    Full Text Available This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN. Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE method to solve the chemical source localization (CSL problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

  14. A practical application combining wireless sensor networks and Internet of Things: Safety Management System for Tower Crane Groups.

    Science.gov (United States)

    Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

    2014-07-30

    The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.

  15. Combining Image and Non-Image Data for Automatic Detection of Retina Disease in a Telemedicine Network

    Energy Technology Data Exchange (ETDEWEB)

    Aykac, Deniz [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK); Fox, Karen [Delta Health Alliance; Garg, Seema [University of North Carolina; Giancardo, Luca [ORNL; Karnowski, Thomas Paul [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Nichols, Trent L [ORNL; Tobin Jr, Kenneth William [ORNL

    2011-01-01

    A telemedicine network with retina cameras and automated quality control, physiological feature location, and lesion/anomaly detection is a low-cost way of achieving broad-based screening for diabetic retinopathy (DR) and other eye diseases. In the process of a routine eye-screening examination, other non-image data is often available which may be useful in automated diagnosis of disease. In this work, we report on the results of combining this non-image data with image data, using the protocol and processing steps of a prototype system for automated disease diagnosis of retina examinations from a telemedicine network. The system includes quality assessments, automated physiology detection, and automated lesion detection to create an archive of known cases. Non-image data such as diabetes onset date and hemoglobin A1c (HgA1c) for each patient examination are included as well, and the system is used to create a content-based image retrieval engine capable of automated diagnosis of disease into 'normal' and 'abnormal' categories. The system achieves a sensitivity and specificity of 91.2% and 71.6% using hold-one-out validation testing.

  16. On Singularities and Black Holes in Combination-Driven Models of Technological Innovation Networks.

    Directory of Open Access Journals (Sweden)

    Ricard Solé

    Full Text Available It has been suggested that innovations occur mainly by combination: the more inventions accumulate, the higher the probability that new inventions are obtained from previous designs. Additionally, it has been conjectured that the combinatorial nature of innovations naturally leads to a singularity: at some finite time, the number of innovations should diverge. Although these ideas are certainly appealing, no general models have been yet developed to test the conditions under which combinatorial technology should become explosive. Here we present a generalised model of technological evolution that takes into account two major properties: the number of previous technologies needed to create a novel one and how rapidly technology ages. Two different models of combinatorial growth are considered, involving different forms of ageing. When long-range memory is used and thus old inventions are available for novel innovations, singularities can emerge under some conditions with two phases separated by a critical boundary. If the ageing has a characteristic time scale, it is shown that no singularities will be observed. Instead, a "black hole" of old innovations appears and expands in time, making the rate of invention creation slow down into a linear regime.

  17. On Singularities and Black Holes in Combination-Driven Models of Technological Innovation Networks.

    Science.gov (United States)

    Solé, Ricard; Amor, Daniel R; Valverde, Sergi

    2016-01-01

    It has been suggested that innovations occur mainly by combination: the more inventions accumulate, the higher the probability that new inventions are obtained from previous designs. Additionally, it has been conjectured that the combinatorial nature of innovations naturally leads to a singularity: at some finite time, the number of innovations should diverge. Although these ideas are certainly appealing, no general models have been yet developed to test the conditions under which combinatorial technology should become explosive. Here we present a generalised model of technological evolution that takes into account two major properties: the number of previous technologies needed to create a novel one and how rapidly technology ages. Two different models of combinatorial growth are considered, involving different forms of ageing. When long-range memory is used and thus old inventions are available for novel innovations, singularities can emerge under some conditions with two phases separated by a critical boundary. If the ageing has a characteristic time scale, it is shown that no singularities will be observed. Instead, a "black hole" of old innovations appears and expands in time, making the rate of invention creation slow down into a linear regime.

  18. Prediction of Increasing Production Activities using Combination of Query Aggregation on Complex Events Processing and Neural Network

    Directory of Open Access Journals (Sweden)

    Achmad Arwan

    2016-07-01

    Full Text Available AbstrakProduksi, order, penjualan, dan pengiriman adalah serangkaian event yang saling terkait dalam industri manufaktur. Selanjutnya hasil dari event tersebut dicatat dalam event log. Complex Event Processing adalah metode yang digunakan untuk menganalisis apakah terdapat pola kombinasi peristiwa tertentu (peluang/ancaman yang terjadi pada sebuah sistem, sehingga dapat ditangani secara cepat dan tepat. Jaringan saraf tiruan adalah metode yang digunakan untuk mengklasifikasi data peningkatan proses produksi. Hasil pencatatan rangkaian proses yang menyebabkan peningkatan produksi digunakan sebagai data latih untuk mendapatkan fungsi aktivasi dari jaringan saraf tiruan. Penjumlahan hasil catatan event log dimasukkan ke input jaringan saraf tiruan untuk perhitungan nilai aktivasi. Ketika nilai aktivasi lebih dari batas yang ditentukan, maka sistem mengeluarkan sinyal untuk meningkatkan produksi, jika tidak, sistem tetap memantau kejadian. Hasil percobaan menunjukkan bahwa akurasi dari metode ini adalah 77% dari 39 rangkaian aliran event.Kata kunci: complex event processing, event, jaringan saraf tiruan, prediksi peningkatan produksi, proses. AbstractProductions, orders, sales, and shipments are series of interrelated events within manufacturing industry. Further these events were recorded in the event log. Complex event processing is a method that used to analyze whether there are patterns of combinations of certain events (opportunities / threats that occur in a system, so it can be addressed quickly and appropriately. Artificial neural network is a method that we used to classify production increase activities. The series of events that cause the increase of the production used as a dataset to train the weight of neural network which result activation value. An aggregate stream of events inserted into the neural network input to compute the value of activation. When the value is over a certain threshold (the activation value results

  19. The fun integration theory: toward sustaining children and adolescents sport participation.

    Science.gov (United States)

    Visek, Amanda J; Achrati, Sara M; Mannix, Heather; McDonnell, Karen; Harris, Brandonn S; DiPietro, Loretta

    2015-03-01

    Children cite "fun" as the primary reason for participation in organized sport and its absence as the number-one reason for youth sport attrition. Therefore, the purpose of this study was to develop a theoretical framework of fun using a novel mixed-method assessment of participants in sport (FUN MAPS) via concept mapping. Youth soccer players (n = 142), coaches (n = 37), and parents (n = 57) were stratified by age, sex, and competition level and contributed their ideas through (a) qualitative brainstorming, identifying all of the things that make playing sports fun for players; (b) sorting of ideas; and (c) rating each idea on its importance, frequency, and feasibility. The FUN MAPS identify the 4 fundamental tenets of fun in youth sport within 11 fun-dimensions composed of 81 specific fun-determinants, while also establishing the youth sport ethos. The FUN MAPS provide pictorial evidence-based blueprints for the fun integration theory (FIT), which is a multitheoretical, multidimensional, and stakeholder derived framework that can be used to maximize fun for children and adolescents to promote and sustain an active and healthy lifestyle through sport.

  20. Making your presentation fun: creative presentation techniques

    Energy Technology Data Exchange (ETDEWEB)

    KEENEN,MARTHA JANE

    2000-05-18

    What possesses someone to volunteer and go through hoops and red tape to make a presentation at a conference? For that matter, why does anyone ever present anything to anyone? Actually, presentations are a fact of life and there are many reasons for doing a presentation and doing it well. New and existing staff need training and orientation to the way things are done here. Handing all of them a manual and hoping they read it is pretty much a waste of paper. On the other hand, an effective, entertaining and upbeat presentation on the relevant topics is more likely to stick with those people. They will even have a name and face to remember and seek out when they have an issue on or with that topic. This can be a very effective beginning for networking with new peers. The presenter is seen as knowledgeable, as a source of information on company topics and possibly evaluated as a potential mentor or future manager. Project staff and/or peers benefit from clear, concise, presentations of topical knowledge. This is one way that a group working on various aspects of the same project or program can stay in touch and in step with each other. Most importantly, presentations may be the best or only door into the minds (and budgets) of management and customers. These presentations are a wonderful opportunity to address legal and compliance issues, budget, staffing, and services. Here is a chance, maybe the only one, to demonstrate and explain the wonderfulness of a program and the benefit they get by using the services offered most effectively. An interactive presentation on legal and compliance issues can be an effective tool in helping customers and/or management make good risk management decisions.

  1. A Nonlinear Modal Aeroelastic Solver for FUN3D

    Science.gov (United States)

    Goldman, Benjamin D.; Bartels, Robert E.; Biedron, Robert T.; Scott, Robert C.

    2016-01-01

    A nonlinear structural solver has been implemented internally within the NASA FUN3D computational fluid dynamics code, allowing for some new aeroelastic capabilities. Using a modal representation of the structure, a set of differential or differential-algebraic equations are derived for general thin structures with geometric nonlinearities. ODEPACK and LAPACK routines are linked with FUN3D, and the nonlinear equations are solved at each CFD time step. The existing predictor-corrector method is retained, whereby the structural solution is updated after mesh deformation. The nonlinear solver is validated using a test case for a flexible aeroshell at transonic, supersonic, and hypersonic flow conditions. Agreement with linear theory is seen for the static aeroelastic solutions at relatively low dynamic pressures, but structural nonlinearities limit deformation amplitudes at high dynamic pressures. No flutter was found at any of the tested trajectory points, though LCO may be possible in the transonic regime.

  2. ONLINE SCAMS: TAKING THE FUN OUT OF THE INTERNET

    OpenAIRE

    Pradeep Kumar Puram; Mukesh Kaparthi; Aditya Krishna Haas Rayaprolu

    2011-01-01

    The fun of using the Internet has become sour due to the various scams taking place day in and day out, all around the world. Internet users are being trapped around every corner and their credit card information is being siphoned, all due to the presence of these online scams. This paper looks in depth into a few of these scams, and explores a solution to counter this menace.

  3. Evidence for network formation during the carbonization of coal from the combination of rheometry and {sup 1}H NMR techniques

    Energy Technology Data Exchange (ETDEWEB)

    Karen M. Steel; Miguel C. Diaz; John W. Patrick; Colin E. Snape [University of Nottingham, Nottingham (United Kingdom). Nottingham Fuel and Energy Centre, School of Chemical, Environmental and Mining Engineering

    2006-09-15

    High-temperature rheometry and {sup 1}H NMR have been combined to assess the microstructural changes taking place during carbonization of a number of different coals. A linear relationship exists between the logarithm of the material's complex viscosity ({eta}{sup {asterisk}}) and the fraction of hydrogen present in rigid structures ({phi}{sub rh}) for the resolidification region in which the material is liquid-like with small amounts of dispersed solid. The relationship is best characterized by the Arrhenius viscosity equation given by {eta}{sup {asterisk}} = {eta}{sub 0}{sup {asterisk}} exp(({eta}){phi}{sub rh}) where {eta}{sub 0}{sup {asterisk}} is the complex viscosity of the liquid medium and {eta} is the intrinsic viscosity of the resolidified material. Attempts to fit the Krieger-Dougherty suspension equation showed that the solid regions formed do not pack together like a normal suspension. Instead, it is more likely that cross-linking and cyclization reactions within the liquid medium give rise to a network structure of solid material and a characteristic gel point. The ratio of hydrogen present in rigid structures to that still present in liquid form at the gel point is approximately 2:3. The resolidified material was found to have a higher {eta} than the components of the coal that remained unsoftened, which suggests that while the unsoftened components have a fairly equant shape, the resolidified components have a much higher hydrodynamic volume. The resolidification process bears similarity with thermosetting polymer networks and the measurements taken for a blend of two coals follow a common two-component polymer blending rule. 35 refs., 13 figs., 4 tabs.

  4. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  5. The Fun Integration Theory: Towards Sustaining Children and Adolescents Sport Participation

    Science.gov (United States)

    Visek, Amanda J.; Achrati, Sara M.; Manning, Heather; McDonnell, Karen; Harris, Brandonn S.; DiPietro, Loretta

    2014-01-01

    BACKGROUND Children cite ‘fun’ as the primary reason for participation in organized sport and its absence as the number one reason for youth sport attrition. Therefore, the purpose of this study was to develop a theoretical framework of fun using a novel mixed-method assessment of participants in sport (FUN MAPS) via concept mapping. METHODS Youth soccer players (n = 142), coaches (n = 37), and parents (n = 57) were stratified by age, sex, and competition level and contributed their “fun” ideas through: (a) qualitative brainstorming, identifying all of the things that make playing sports fun for players; (b) sorting of ideas; and (c) rating each idea on its importance, frequency, and feasibility. RESULTS The FUN MAPS identify the four fundamental tenets of fun in youth sport within 11 fun-dimensions composed of 81 specific fun-determinants, while also establishing the youth sport ethos. CONCLUSION The FUN MAPS provide pictorial evidence-based blueprints for the fun integration theory (FIT), which is a multi-theoretical, multidimensional, and stakeholder derived framework that can be used to maximize fun for children and adolescents in order to promote and sustain an active and healthy lifestyle through sport. PMID:24770788

  6. This is Not a Game - Social Virtual Worlds, Fun, and Learning

    Science.gov (United States)

    Bell, Mark W.; Smith-Robbins, Sarah; Withnail, Greg

    This chapter asks a simple question: what is required to make learning fun in social virtual worlds? Several scholars have connected fun with learning but most of these have centered on the function of games in learning. Studies of learning in massive multiplayer online role playing games connect the game mechanics to how learning occurs. However, few have asked whether learning in a virtual world can be fun if there is no game. In a social virtual world, like Second Life (SL) there are no game mechanics (unlike game worlds like World of Warcraft [WoW]). There are no quests, challenges, rewards or other game elements in SL. So can a virtual world that has no game-content provided be a place where fun learning can take place? We define fun and explore how fun has been related to learning. We explore theories of fun from Koster, Crawford, Csíkszentmihályi and others as well as views of the ways fun is explored as related to the learning experience. With these models in mind, we explore how fun is different in a social virtual world. Drawing on definitions of fun from Castronova and others, we see game structures in virtual worlds may not be needed to have fun. These fun activities include game creation, business interactions, and most importantly, identity play and socialization in a social virtual world. Finally, we propose that if learning is to be successful and fun in a social virtual world it should pay close attention to these two activities.

  7. Sharing network resources

    CERN Document Server

    Parekh, Abhay

    2014-01-01

    Resource Allocation lies at the heart of network control. In the early days of the Internet the scarcest resource was bandwidth, but as the network has evolved to become an essential utility in the lives of billions, the nature of the resource allocation problem has changed. This book attempts to describe the facets of resource allocation that are most relevant to modern networks. It is targeted at graduate students and researchers who have an introductory background in networking and who desire to internalize core concepts before designing new protocols and applications. We start from the fun

  8. Online monitoring and conditional regression tree test: Useful tools for a better understanding of combined sewer network behavior.

    Science.gov (United States)

    Bersinger, T; Bareille, G; Pigot, T; Bru, N; Le Hécho, I

    2018-06-01

    A good knowledge of the dynamic of pollutant concentration and flux in a combined sewer network is necessary when considering solutions to limit the pollutants discharged by combined sewer overflow (CSO) into receiving water during wet weather. Identification of the parameters that influence pollutant concentration and flux is important. Nevertheless, few studies have obtained satisfactory results for the identification of these parameters using statistical tools. Thus, this work uses a large database of rain events (116 over one year) obtained via continuous measurement of rainfall, discharge flow and chemical oxygen demand (COD) estimated using online turbidity for the identification of these parameters. We carried out a statistical study of the parameters influencing the maximum COD concentration, the discharge flow and the discharge COD flux. In this study a new test was used that has never been used in this field: the conditional regression tree test. We have demonstrated that the antecedent dry weather period, the rain event average intensity and the flow before the event are the three main factors influencing the maximum COD concentration during a rainfall event. Regarding the discharge flow, it is mainly influenced by the overall rainfall height but not by the maximum rainfall intensity. Finally, COD discharge flux is influenced by the discharge volume and the maximum COD concentration. Regression trees seem much more appropriate than common tests like PCA and PLS for this type of study as they take into account the thresholds and cumulative effects of various parameters as a function of the target variable. These results could help to improve sewer and CSO management in order to decrease the discharge of pollutants into receiving waters. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Hallucination- and speech-specific hypercoupling in frontotemporal auditory and language networks in schizophrenia using combined task-based fMRI data: An fBIRN study.

    Science.gov (United States)

    Lavigne, Katie M; Woodward, Todd S

    2018-04-01

    Hypercoupling of activity in speech-perception-specific brain networks has been proposed to play a role in the generation of auditory-verbal hallucinations (AVHs) in schizophrenia; however, it is unclear whether this hypercoupling extends to nonverbal auditory perception. We investigated this by comparing schizophrenia patients with and without AVHs, and healthy controls, on task-based functional magnetic resonance imaging (fMRI) data combining verbal speech perception (SP), inner verbal thought generation (VTG), and nonverbal auditory oddball detection (AO). Data from two previously published fMRI studies were simultaneously analyzed using group constrained principal component analysis for fMRI (group fMRI-CPCA), which allowed for comparison of task-related functional brain networks across groups and tasks while holding the brain networks under study constant, leading to determination of the degree to which networks are common to verbal and nonverbal perception conditions, and which show coordinated hyperactivity in hallucinations. Three functional brain networks emerged: (a) auditory-motor, (b) language processing, and (c) default-mode (DMN) networks. Combining the AO and sentence tasks allowed the auditory-motor and language networks to separately emerge, whereas they were aggregated when individual tasks were analyzed. AVH patients showed greater coordinated activity (deactivity for DMN regions) than non-AVH patients during SP in all networks, but this did not extend to VTG or AO. This suggests that the hypercoupling in AVH patients in speech-perception-related brain networks is specific to perceived speech, and does not extend to perceived nonspeech or inner verbal thought generation. © 2017 Wiley Periodicals, Inc.

  10. Economic competitiveness of underground coal gasification combined with carbon capture and storage in the Bulgarian energy network

    Energy Technology Data Exchange (ETDEWEB)

    Nakaten, Natalie Christine

    2014-11-15

    Underground coal gasification (UCG) allows for exploitation of deep-seated coal seams not economically exploitable by conventional coal mining. Aim of the present study is to examine UCG economics based on coal conversion into a synthesis gas to fuel a combined cycle gas turbine power plant (CCGT) with CO2 capture and storage (CCS). Thereto, a techno-economic model is developed for UCG-CCGT-CCS costs of electricity (COE) determination which, considering sitespecific data of a selected target area in Bulgaria, sum up to 72 Euro/MWh in total. To quantify the impact of model constraints on COE, sensitivity analyses are undertaken revealing that varying geological model constraints impact COE with 0.4% to 4%, chemical with 13%, technical with 8% to 17% and market-dependent with 2% to 25%. Besides site-specific boundary conditions, UCG-CCGT-CCS economics depend on resources availability and infrastructural characteristics of the overall energy system. Assessing a model based implementation of UCG-CCGT-CCS and CCS power plants into the Bulgarian energy network revealed that both technologies provide essential and economically competitive options to achieve the EU environmental targets and a complete substitution of gas imports by UCG synthesis gas production.

  11. Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.

    Science.gov (United States)

    Bail, Christopher Andrew

    2016-10-18

    Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-ranging conversation among social media users, whereas the vast majority of them receive little or no attention. I argue that advocacy organizations are more likely to inspire comments from new social media audiences if they create "cultural bridges," or produce messages that combine conversational themes within an advocacy field that are seldom discussed together. I use natural language processing, network analysis, and a social media application to analyze how cultural bridges shaped public discourse about autism spectrum disorders on Facebook over the course of 1.5 years, controlling for various characteristics of advocacy organizations, their social media audiences, and the broader social context in which they interact. I show that organizations that create substantial cultural bridges provoke 2.52 times more comments about their messages from new social media users than those that do not, controlling for these factors. This study thus offers a theory of cultural messaging and public deliberation and computational techniques for text analysis and application-based survey research.

  12. Forecasting of UV-Vis absorbance time series using artificial neural networks combined with principal component analysis.

    Science.gov (United States)

    Plazas-Nossa, Leonardo; Hofer, Thomas; Gruber, Günter; Torres, Andres

    2017-02-01

    This work proposes a methodology for the forecasting of online water quality data provided by UV-Vis spectrometry. Therefore, a combination of principal component analysis (PCA) to reduce the dimensionality of a data set and artificial neural networks (ANNs) for forecasting purposes was used. The results obtained were compared with those obtained by using discrete Fourier transform (DFT). The proposed methodology was applied to four absorbance time series data sets composed by a total number of 5705 UV-Vis spectra. Absolute percentage errors obtained by applying the proposed PCA/ANN methodology vary between 10% and 13% for all four study sites. In general terms, the results obtained were hardly generalizable, as they appeared to be highly dependent on specific dynamics of the water system; however, some trends can be outlined. PCA/ANN methodology gives better results than PCA/DFT forecasting procedure by using a specific spectra range for the following conditions: (i) for Salitre wastewater treatment plant (WWTP) (first hour) and Graz West R05 (first 18 min), from the last part of UV range to all visible range; (ii) for Gibraltar pumping station (first 6 min) for all UV-Vis absorbance spectra; and (iii) for San Fernando WWTP (first 24 min) for all of UV range to middle part of visible range.

  13. Age-related reorganization of functional networks for successful conflict resolution: a combined functional and structural MRI study.

    Science.gov (United States)

    Schulte, Tilman; Müller-Oehring, Eva M; Chanraud, Sandra; Rosenbloom, Margaret J; Pfefferbaum, Adolf; Sullivan, Edith V

    2011-11-01

    Aging has readily observable effects on the ability to resolve conflict between competing stimulus attributes that are likely related to selective structural and functional brain changes. To identify age-related differences in neural circuits subserving conflict processing, we combined structural and functional MRI and a Stroop Match-to-Sample task involving perceptual cueing and repetition to modulate resources in healthy young and older adults. In our Stroop Match-to-Sample task, older adults handled conflict by activating a frontoparietal attention system more than young adults and engaged a visuomotor network more than young adults when processing repetitive conflict and when processing conflict following valid perceptual cueing. By contrast, young adults activated frontal regions more than older adults when processing conflict with perceptual cueing. These differential activation patterns were not correlated with regional gray matter volume despite smaller volumes in older than young adults. Given comparable performance in speed and accuracy of responding between both groups, these data suggest that successful aging is associated with functional reorganization of neural systems to accommodate functionally increasing task demands on perceptual and attentional operations. Copyright © 2009 Elsevier Inc. All rights reserved.

  14. Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction.

    Science.gov (United States)

    Zhao, Di; Weng, Chunhua

    2011-10-01

    In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

  15. A normalization method for combination of laboratory test results from different electronic healthcare databases in a distributed research network.

    Science.gov (United States)

    Yoon, Dukyong; Schuemie, Martijn J; Kim, Ju Han; Kim, Dong Ki; Park, Man Young; Ahn, Eun Kyoung; Jung, Eun-Young; Park, Dong Kyun; Cho, Soo Yeon; Shin, Dahye; Hwang, Yeonsoo; Park, Rae Woong

    2016-03-01

    Distributed research networks (DRNs) afford statistical power by integrating observational data from multiple partners for retrospective studies. However, laboratory test results across care sites are derived using different assays from varying patient populations, making it difficult to simply combine data for analysis. Additionally, existing normalization methods are not suitable for retrospective studies. We normalized laboratory results from different data sources by adjusting for heterogeneous clinico-epidemiologic characteristics of the data and called this the subgroup-adjusted normalization (SAN) method. Subgroup-adjusted normalization renders the means and standard deviations of distributions identical under population structure-adjusted conditions. To evaluate its performance, we compared SAN with existing methods for simulated and real datasets consisting of blood urea nitrogen, serum creatinine, hematocrit, hemoglobin, serum potassium, and total bilirubin. Various clinico-epidemiologic characteristics can be applied together in SAN. For simplicity of comparison, age and gender were used to adjust population heterogeneity in this study. In simulations, SAN had the lowest standardized difference in means (SDM) and Kolmogorov-Smirnov values for all tests (p normalization performed better than normalization using other methods. The SAN method is applicable in a DRN environment and should facilitate analysis of data integrated across DRN partners for retrospective observational studies. Copyright © 2015 John Wiley & Sons, Ltd.

  16. A robust observer based on H∞ filtering with parameter uncertainties combined with Neural Networks for estimation of vehicle roll angle

    Science.gov (United States)

    Boada, Beatriz L.; Boada, Maria Jesus L.; Vargas-Melendez, Leandro; Diaz, Vicente

    2018-01-01

    Nowadays, one of the main objectives in road transport is to decrease the number of accident victims. Rollover accidents caused nearly 33% of all deaths from passenger vehicle crashes. Roll Stability Control (RSC) systems prevent vehicles from untripped rollover accidents. The lateral load transfer is the main parameter which is taken into account in the RSC systems. This parameter is related to the roll angle, which can be directly measured from a dual-antenna GPS. Nevertheless, this is a costly technique. For this reason, roll angle has to be estimated. In this paper, a novel observer based on H∞ filtering in combination with a neural network (NN) for the vehicle roll angle estimation is proposed. The design of this observer is based on four main criteria: to use a simplified vehicle model, to use signals of sensors which are installed onboard in current vehicles, to consider the inaccuracy in the system model and to attenuate the effect of the external disturbances. Experimental results show the effectiveness of the proposed observer.

  17. Economic competitiveness of underground coal gasification combined with carbon capture and storage in the Bulgarian energy network

    International Nuclear Information System (INIS)

    Nakaten, Natalie Christine

    2014-01-01

    Underground coal gasification (UCG) allows for exploitation of deep-seated coal seams not economically exploitable by conventional coal mining. Aim of the present study is to examine UCG economics based on coal conversion into a synthesis gas to fuel a combined cycle gas turbine power plant (CCGT) with CO2 capture and storage (CCS). Thereto, a techno-economic model is developed for UCG-CCGT-CCS costs of electricity (COE) determination which, considering sitespecific data of a selected target area in Bulgaria, sum up to 72 Euro/MWh in total. To quantify the impact of model constraints on COE, sensitivity analyses are undertaken revealing that varying geological model constraints impact COE with 0.4% to 4%, chemical with 13%, technical with 8% to 17% and market-dependent with 2% to 25%. Besides site-specific boundary conditions, UCG-CCGT-CCS economics depend on resources availability and infrastructural characteristics of the overall energy system. Assessing a model based implementation of UCG-CCGT-CCS and CCS power plants into the Bulgarian energy network revealed that both technologies provide essential and economically competitive options to achieve the EU environmental targets and a complete substitution of gas imports by UCG synthesis gas production.

  18. Alcoholic fermentation under oenological conditions. Use of a combination of data analysis and neural networks to predict sluggish and stuck fermentations

    Energy Technology Data Exchange (ETDEWEB)

    Insa, G. [Inst. National de la Recherche Agronomique, Inst. des Produits de la Vigne, Lab. de Microbiologie et Technologie des Fermentations, 34 - Montpellier (France); Sablayrolles, J.M. [Inst. National de la Recherche Agronomique, Inst. des Produits de la Vigne, Lab. de Microbiologie et Technologie des Fermentations, 34 - Montpellier (France); Douzal, V. [Centre National du Machinisme Agricole du Genie Rural des Eaux et Forets, 92 - Antony (France)

    1995-09-01

    The possibility of predicting sluggish fermentations under oenological conditions was investigated by studying 117 musts of different French grape varieties using an automatic device for fermentation monitoring. The objective was to detect sluggish or stuck fermentations at the halfway point of fermentation. Seventy nine percent of fermentations were correctly predicted by combining data analysis and neural networks. (orig.)

  19. Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution.

    Directory of Open Access Journals (Sweden)

    Amanda Tse

    Full Text Available Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib and promiscuous (Bosutinib, Dasatinib kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations

  20. Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution

    Science.gov (United States)

    Tse, Amanda; Verkhivker, Gennady M.

    2015-01-01

    Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib) and promiscuous (Bosutinib, Dasatinib) kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations of key mediating

  1. Combination of DTI and fMRI reveals the white matter changes correlating with the decline of default-mode network activity in Alzheimer's disease

    Science.gov (United States)

    Wu, Xianjun; Di, Qian; Li, Yao; Zhao, Xiaojie

    2009-02-01

    Recently, evidences from fMRI studies have shown that there was decreased activity among the default-mode network in Alzheimer's disease (AD), and DTI researches also demonstrated that demyelinations exist in white matter of AD patients. Therefore, combining these two MRI methods may help to reveal the relationship between white matter damages and alterations of the resting state functional connectivity network. In the present study, we tried to address this issue by means of correlation analysis between DTI and resting state fMRI images. The default-mode networks of AD and normal control groups were compared to find the areas with significantly declined activity firstly. Then, the white matter regions whose fractional anisotropy (FA) value correlated with this decline were located through multiple regressions between the FA values and the BOLD response of the default networks. Among these correlating white matter regions, those whose FA values also declined were found by a group comparison between AD patients and healthy elderly control subjects. Our results showed that the areas with decreased activity among default-mode network included left posterior cingulated cortex (PCC), left medial temporal gyrus et al. And the damaged white matter areas correlated with the default-mode network alterations were located around left sub-gyral temporal lobe. These changes may relate to the decreased connectivity between PCC and medial temporal lobe (MTL), and thus correlate with the deficiency of default-mode network activity.

  2. Water balance estimation in high Alpine terrain by combining distributed modeling and a neural network approach (Berchtesgaden Alps, Germany

    Directory of Open Access Journals (Sweden)

    G. Kraller

    2012-07-01

    Full Text Available The water balance in high Alpine regions is often characterized by significant variation of meteorological variables in space and time, a complex hydrogeological situation and steep gradients. The system is even more complex when the rock composition is dominated by soluble limestone, because unknown underground flow conditions and flow directions lead to unknown storage quantities. Reliable distributed modeling cannot be implemented by traditional approaches due to unknown storage processes at local and catchment scale. We present an artificial neural network extension of a distributed hydrological model (WaSiM-ETH that allows to account for subsurface water transfer in a karstic environment. The extension was developed for the Alpine catchment of the river "Berchtesgadener Ache" (Berchtesgaden Alps, Germany, which is characterized by extreme topography and calcareous rocks. The model assumes porous conditions and does not account for karstic environments, resulting in systematic mismatch of modeled and measured runoff in discharge curves at the outlet points of neighboring high alpine subbasins. Various precipitation interpolation methods did not allow to explain systematic mismatches, and unknown subsurface hydrological processes were concluded as the underlying reason. We introduce a new method that allows to describe the unknown subsurface boundary fluxes, and account for them in the hydrological model. This is achieved by an artificial neural network approach (ANN, where four input variables are taken to calculate the unknown subsurface storage conditions. This was first developed for the high Alpine subbasin Königsseer Ache to improve the monthly water balance. We explicitly derive the algebraic transfer function of an artificial neural net to calculate the missing boundary fluxes. The result of the ANN is then implemented in the groundwater module of the hydrological model as boundary flux, and considered during the consecutive model

  3. Improved diagnostic accuracy of Alzheimer's disease by combining regional cortical thickness and default mode network functional connectivity: Validated in the Alzheimer's disease neuroimaging initiative set

    International Nuclear Information System (INIS)

    Park, Ji Eun; Park, Bum Woo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Jung; Oh, Joo Young; Shim, Woo Hyun; Lee, Jae Hong; Roh, Jee Hoon

    2017-01-01

    To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease

  4. Manufacturing leisure - Innovations in happiness, well-being and fun

    OpenAIRE

    Pantzar, Mika; Shove, Elizabeth

    2005-01-01

    Kulutus ja vapaa-ajan talous ovat nousseet useissa länsimaissa elinkeinopoliittisen keskustelun huomion kohteeksi viime vuosina. Talouden kasvu on nähty yhä enemmän tapahtuvan ns. elämystalouden ja viihdeteollisuuden virittämänä. Manufacturing leisure - Innovations in happiness, well-being and fun lähestyy vapaa-ajan klusteria kuluttajien vapaa-ajan käytäntöjen näkökulmasta. Saksalaiset, englantilaiset ja suomalaiset tutkijat pyrkivät vastaamaan muun muassa seuraaviin kysymyksiin: · Minkälais...

  5. Fun with maths and physics: brain teasers tricks illusions

    CERN Document Server

    Perelman, Yakov

    2013-01-01

    Fun with Maths and Physics details a large number of intriguing physics experiments, entertaining mathematics problems, and amazing optical illusions.The book’s main objective is to arouse the reader’s scientific imagination, teach him to think in a scientific manner, and create in his mind a variety of associations between physical knowledge and a large number of real daily life observations.Immensely instructive and entertaining, it has been one of the best sellers in Russia during the first part of last century.

  6. Efficacy Comparison of Six Chemotherapeutic Combinations for Osteosarcoma and Ewing's Sarcoma Treatment: A Network Meta-Analysis.

    Science.gov (United States)

    Zhang, Tao; Zhang, Song; Yang, Feifei; Wang, Lili; Zhu, Sigang; Qiu, Bing; Li, Shunhua; Deng, Zhongliang

    2018-01-01

    This study aimed to address the insufficiency of traditional meta-analysis and provide improved guidelines for the clinical practice of osteosarcoma treatment. The heterogeneity of the fixed-effect model was calculated, and when necessary, a random-effect model was adopted. Furthermore, the direct and indirect evidence was pooled together and exhibited in the forest plot and slash table. The surface under the cumulative ranking curve (SUCRA) value was also measured to rank each intervention. Finally, heat plot was introduced to demonstrate the contribution of each intervention and the inconsistency between direct and indirect comparisons. This network meta-analysis included 32 trials, involving a total of 5,626 subjects reported by 28 articles. All the treatments were classified into six chemotherapeutic combinations: dual agent with or without ifosfamide (IFO), multi-agent with or without IFO, and dual agent or multi-agent with IFO and etoposide. For the primary outcomes, both overall survival (OS) and event-free survival (EFS) rates were considered. The multi-agent integrated with IFO and etoposide showed an optimal performance for 5-year OS, 10-year OS, 3-year EFS, 5-year EFS, and 10-year EFS when compared with placebo. The SUCRA value of this treatment was also the highest of these six interventions. However, multi-drug with IFO alone had the highest SUCRA value of 0.652 and 0.516 when it came to relapse and lung-metastasis. It was efficient to some extent, but no significant difference was observed in both outcomes. Chemotherapy, applied as induction or adjuvant treatment with radiation therapy or surgery, is able to increase the survival rate of patients, especially by combining multi-drug with IFO and etoposide, which demonstrated the best performance in both OS and EFS. As for relapse and the lung-metastasis, multiple agents with IFO alone seemed to have the optimal efficiency, although no significant difference was observed here. J. Cell. Biochem. 119: 250

  7. Structural and functional abnormalities of default mode network in minimal hepatic encephalopathy: a study combining DTI and fMRI.

    Directory of Open Access Journals (Sweden)

    Rongfeng Qi

    Full Text Available BACKGROUND AND PURPOSE: Live failure can cause brain edema and aberrant brain function in cirrhotic patients. In particular, decreased functional connectivity within the brain default-mode network (DMN has been recently reported in overt hepatic encephalopathy (HE patients. However, so far, little is known about the connectivity among the DMN in the minimal HE (MHE, the mildest form of HE. Here, we combined diffusion tensor imaging (DTI and resting-state functional MRI (rs-fMRI to test our hypothesis that both structural and functional connectivity within the DMN were disturbed in MHE. MATERIALS AND METHODS: Twenty MHE patients and 20 healthy controls participated in the study. We explored the changes of structural (path length, tracts count, fractional anisotropy [FA] and mean diffusivity [MD] derived from DTI tractography and functional (temporal correlation coefficient derived from rs-fMRI connectivity of the DMN in MHE patients. Pearson correlation analysis was performed between the structural/functional indices and venous blood ammonia levels/neuropsychological tests scores of patients. All thresholds were set at P<0.05, Bonferroni corrected. RESULTS: Compared to the healthy controls, MHE patients showed both decreased FA and increased MD in the tract connecting the posterior cingulate cortex/precuneus (PCC/PCUN to left parahippocampal gyrus (PHG, and decreased functional connectivity between the PCC/PCUN and left PHG, and medial prefrontal cortex (MPFC. MD values of the tract connecting PCC/PCUN to the left PHG positively correlated to the ammonia levels, the temporal correlation coefficients between the PCC/PCUN and the MPFC showed positive correlation to the digital symbol tests scores of patients. CONCLUSION: MHE patients have both disturbed structural and functional connectivity within the DMN. The decreased functional connectivity was also detected between some regions without abnormal structural connectivity, suggesting that the

  8. Comparative efficacy of inhaled corticosteroid and long-acting beta agonist combinations in preventing COPD exacerbations: a Bayesian network meta-analysis.

    Science.gov (United States)

    Oba, Yuji; Lone, Nazir A

    2014-01-01

    A combination therapy with inhaled corticosteroid (ICS) and a long-acting beta agonist (LABA) is recommended in severe chronic obstructive pulmonary disease (COPD) patients experiencing frequent exacerbations. Currently, there are five ICS/LABA combination products available on the market. The purpose of this study was to systematically review the efficacy of various ICS/LABA combinations with a network meta-analysis. Several databases and manufacturer's websites were searched for relevant clinical trials. Randomized control trials, at least 12 weeks duration, comparing an ICS/LABA combination with active control or placebo were included. Moderate and severe exacerbations were chosen as the outcome assessment criteria. The primary analyses were conducted with a Bayesian Markov chain Monte Carlo method. Most of the ICS/LABA combinations reduced moderate-to-severe exacerbations as compared with placebo and LABA, but none of them reduced severe exacerbations. However, many studies excluded patients receiving long-term oxygen therapy. Moderate-dose ICS was as effective as high-dose ICS in reducing exacerbations when combined with LABA. ICS/LABA combinations had a class effect with regard to the prevention of COPD exacerbations. Moderate-dose ICS/LABA combination therapy would be sufficient for COPD patients when indicated. The efficacy of ICS/LABA combination therapy appeared modest and had no impact in reducing severe exacerbations. Further studies are needed to evaluate the efficacy of ICS/LABA combination therapy in severely affected COPD patients requiring long-term oxygen therapy.

  9. Waiting as Part of the Fun: Interactive Gaming in Theme Park Queues

    NARCIS (Netherlands)

    Heger, Chris; Offermans, S.A.M.; Frens, J.W.; Wouters, I.H.C.; Kimman, F.P.F.; Tieben, R.; Offermans, S.A.M.; Nagtzaam, H.A.H.

    2009-01-01

    People visiting theme parks intend to have a day of fun. Yet a larger part of the time is spent queuing for rides rather than in the actual rides, which does not contribute to the intended fun experience. Current efforts therefore either make the queue as bearable as possible or try to get rid of it

  10. Top 10 Reasons Why Children Find Physical Activity to Be Fun

    Science.gov (United States)

    Hopple, Christine J.

    2018-01-01

    "Fun" is considered, from both research and practical knowledge, to be a critical factor in children's decision to participate (or not) in physical activity (PA). Despite its importance, few studies have provided in-depth investigations into what children really mean when they say an activity is fun. The purpose of this article is to…

  11. Prediction of phenotypic susceptibility to antiretroviral drugs using physiochemical properties of the primary enzymatic structure combined with artificial neural networks

    DEFF Research Database (Denmark)

    Kjaer, J; Høj, L; Fox, Z

    2008-01-01

    OBJECTIVES: Genotypic interpretation systems extrapolate observed associations in datasets to predict viral susceptibility to antiretroviral drugs (ARVs) for given isolates. We aimed to develop and validate an approach using artificial neural networks (ANNs) that employ descriptors...

  12. Frequency of victimization experiences and well-being among online, offline and combined victims on social online network sites of German children and adolescents

    Directory of Open Access Journals (Sweden)

    Michael eGlüer

    2015-12-01

    Full Text Available Victimization is associated with negative developmental outcomes in childhood and adolescence. However, previous studies have provided mixed results regarding the association between offline and online victimization and indicators of social, psychological, and somatic well-being. In this study, we investigated 1,906 German children and adolescents (grades 5 to 10, mean age = 13.9; SD = 2.1 with and without offline or online victimization experiences who participated in a social online network (SNS. Online questionnaires were used to assess previous victimization (offline, online, combined, and without, somatic and psychological symptoms, self-esteem, and social self-concept (social competence, resistance to peer influence, esteem by others. In total, 1,362 (71.4% children and adolescents reported being a member of at least one social online network, and 377 students (28.8% reported previous victimization. Most children and adolescents had offline victimization experiences (17.5%, whereas 2.7% reported online victimization, and 8.6% reported combined experiences. Girls reported more online and combined victimization, and boys reported more offline victimization. The type of victimization (offline, online, combined was associated with increased reports of psychological and somatic symptoms, lower self-esteem and esteem by others, and lower resistance to peer influences. The effects were comparable for the groups with offline and online victimization. They were, however, increased in the combined group in comparison to victims with offline experiences alone.

  13. Exploring patterns of alteration in Alzheimer’s disease brain networks: a combined structural and functional connectomics analysis

    Directory of Open Access Journals (Sweden)

    Fulvia Palesi

    2016-09-01

    Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder characterized by a severe derangement of cognitive functions, primarily memory, in elderly subjects. As far as the functional impairment is concerned, growing evidence supports the disconnection syndrome hypothesis. Recent investigations using fMRI have revealed a generalized alteration of resting state networks in patients affected by AD and mild cognitive impairment (MCI. However, it was unclear whether the changes in functional connectivity were accompanied by corresponding structural network changes. In this work, we have developed a novel structural/functional connectomic approach: resting state fMRI was used to identify the functional cortical network nodes and diffusion MRI to reconstruct the fiber tracts to give a weight to internodal subcortical connections. Then, local and global efficiency were determined for different networks, exploring specific alterations of integration and segregation patterns in AD and MCI patients compared to healthy controls (HC. In the default mode network (DMN, that was the most affected, axonal loss and reduced axonal integrity appeared to compromise both local and global efficiency along posterior-anterior connections. In the basal ganglia network (BGN, disruption of white matter integrity implied that main alterations occurred in local microstructure. In the anterior insular network (AIN, neuronal loss probably subtended a compromised communication with the insular cortex. Cognitive performance, evaluated by neuropsychological examinations, revealed a dependency on integration and segregation of brain networks. These findings are indicative of the fact that cognitive deficits in AD could be associated not only with cortical alterations (revealed by fMRI but also with subcortical alterations (revealed by diffusion MRI that extend beyond the areas primarily damaged by neurodegeneration, towards the support of an emerging concept of AD as a

  14. Precise deformation measurement of prestressed concrete beam during a strain test using the combination of intersection photogrammetry and micro-network measurement

    Science.gov (United States)

    Urban, Rudolf; Braun, Jaroslav; Štroner, Martin

    2015-05-01

    The prestressed thin-walled concrete elements enable the bridge a relatively large span. These structures are advantageous in economic and environmental way due to their thickness and lower consumption of materials. The bending moments can be effectively influenced by using the pre-stress. The experiment was done to monitor deformation of the under load. During the experiment the discrete points were monitored. To determine a large number of points, the intersection photogrammetry combined with precise micro-network were chosen. Keywords:

  15. Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network

    Directory of Open Access Journals (Sweden)

    Michelle Wong

    2018-03-01

    Full Text Available Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

  16. The SNF2-family member Fun30 promotes gene silencing in heterochromatic loci.

    Directory of Open Access Journals (Sweden)

    Ana Neves-Costa

    2009-12-01

    Full Text Available Chromatin regulates many key processes in the nucleus by controlling access to the underlying DNA. SNF2-like factors are ATP-driven enzymes that play key roles in the dynamics of chromatin by remodelling nucleosomes and other nucleoprotein complexes. Even simple eukaryotes such as yeast contain members of several subfamilies of SNF2-like factors. The FUN30/ETL1 subfamily of SNF2 remodellers is conserved from yeasts to humans, but is poorly characterized. We show that the deletion of FUN30 leads to sensitivity to the topoisomerase I poison camptothecin and to severe cell cycle progression defects when the Orc5 subunit is mutated. We demonstrate a role of FUN30 in promoting silencing in the heterochromatin-like mating type locus HMR, telomeres and the rDNA repeats. Chromatin immunoprecipitation experiments demonstrate that Fun30 binds at the boundary element of the silent HMR and within the silent HMR. Mapping of nucleosomes in vivo using micrococcal nuclease demonstrates that deletion of FUN30 leads to changes of the chromatin structure at the boundary element. A point mutation in the ATP-binding site abrogates the silencing function of Fun30 as well as its toxicity upon overexpression, indicating that the ATPase activity is essential for these roles of Fun30. We identify by amino acid sequence analysis a putative CUE motif as a feature of FUN30/ETL1 factors and show that this motif assists Fun30 activity. Our work suggests that Fun30 is directly involved in silencing by regulating the chromatin structure within or around silent loci.

  17. Breaking with fun, educational and realistic learning games

    DEFF Research Database (Denmark)

    Duus Henriksen, Thomas

    2009-01-01

    are commonly conceived as means for staging learning processes, and that thinking learning games so has an inhibiting effect in regard to creating learning processes. The paper draws upon a qualitative study of participants' experiences with ‘the EIS Simulation', which is a computer-based learning game......This paper addresses the game conceptions and values that learning games inherit from regular gaming, as well as how they affect the use and development of learning games. Its key points concern the issues of thinking learning games as fun, educative and realistic, which is how learning games...... for teaching change management and change implementation. The EIS is played in groups, who share the game on a computer, and played by making change decisions in order to implement an IT system in an organisation. In this study, alternative participatory incentives, means for creating learning processes...

  18. Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Lei Feng

    2018-06-01

    Full Text Available Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874–1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN, evolutionary neural network (ENN, extreme learning machine (ELM, general regression neural network (GRNN and radial basis neural network (RBNN were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts.

  19. FunGene: the functional gene pipeline and repository.

    Science.gov (United States)

    Fish, Jordan A; Chai, Benli; Wang, Qiong; Sun, Yanni; Brown, C Titus; Tiedje, James M; Cole, James R

    2013-01-01

    Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

  20. FunGene: the Functional Gene Pipeline and Repository

    Directory of Open Access Journals (Sweden)

    Jordan A. Fish

    2013-10-01

    Full Text Available Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer.While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/ offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

  1. Assessing Fun Items' Effectiveness in Increasing Learning of College Introductory Statistics Students: Results of a Randomized Experiment

    Science.gov (United States)

    Lesser, Lawrence M.; Pearl, Dennis K.; Weber, John J., III

    2016-01-01

    There has been a recent emergence of scholarship on the use of fun in the college statistics classroom, with at least 20 modalities identified. While there have been randomized experiments that suggest that fun can enhance student achievement or attitudes in statistics, these studies have generally been limited to one particular fun modality or…

  2. Fiber-wireless integrated mobile backhaul network based on a hybrid millimeter-wave and free-space-optics architecture with an adaptive diversity combining technique.

    Science.gov (United States)

    Zhang, Junwen; Wang, Jing; Xu, Yuming; Xu, Mu; Lu, Feng; Cheng, Lin; Yu, Jianjun; Chang, Gee-Kung

    2016-05-01

    We propose and experimentally demonstrate a novel fiber-wireless integrated mobile backhaul network based on a hybrid millimeter-wave (MMW) and free-space-optics (FSO) architecture using an adaptive combining technique. Both 60 GHz MMW and FSO links are demonstrated and fully integrated with optical fibers in a scalable and cost-effective backhaul system setup. Joint signal processing with an adaptive diversity combining technique (ADCT) is utilized at the receiver side based on a maximum ratio combining algorithm. Mobile backhaul transportation of 4-Gb/s 16 quadrature amplitude modulation frequency-division multiplexing (QAM-OFDM) data is experimentally demonstrated and tested under various weather conditions synthesized in the lab. Performance improvement in terms of reduced error vector magnitude (EVM) and enhanced link reliability are validated under fog, rain, and turbulence conditions.

  3. Effects of the distribution density of a biomass combined heat and power plant network on heat utilisation efficiency in village-town systems.

    Science.gov (United States)

    Zhang, Yifei; Kang, Jian

    2017-11-01

    The building of biomass combined heat and power (CHP) plants is an effective means of developing biomass energy because they can satisfy demands for winter heating and electricity consumption. The purpose of this study was to analyse the effect of the distribution density of a biomass CHP plant network on heat utilisation efficiency in a village-town system. The distribution density is determined based on the heat transmission threshold, and the heat utilisation efficiency is determined based on the heat demand distribution, heat output efficiency, and heat transmission loss. The objective of this study was to ascertain the optimal value for the heat transmission threshold using a multi-scheme comparison based on an analysis of these factors. To this end, a model of a biomass CHP plant network was built using geographic information system tools to simulate and generate three planning schemes with different heat transmission thresholds (6, 8, and 10 km) according to the heat demand distribution. The heat utilisation efficiencies of these planning schemes were then compared by calculating the gross power, heat output efficiency, and heat transmission loss of the biomass CHP plant for each scenario. This multi-scheme comparison yielded the following results: when the heat transmission threshold was low, the distribution density of the biomass CHP plant network was high and the biomass CHP plants tended to be relatively small. In contrast, when the heat transmission threshold was high, the distribution density of the network was low and the biomass CHP plants tended to be relatively large. When the heat transmission threshold was 8 km, the distribution density of the biomass CHP plant network was optimised for efficient heat utilisation. To promote the development of renewable energy sources, a planning scheme for a biomass CHP plant network that maximises heat utilisation efficiency can be obtained using the optimal heat transmission threshold and the nonlinearity

  4. Resilience to climate change in a cross-scale tourism governance context: a combined quantitative-qualitative network analysis

    Directory of Open Access Journals (Sweden)

    Tobias Luthe

    2016-03-01

    Full Text Available Social systems in mountain regions are exposed to a number of disturbances, such as climate change. Calls for conceptual and practical approaches on how to address climate change have been taken up in the literature. The resilience concept as a comprehensive theory-driven approach to address climate change has only recently increased in importance. Limited research has been undertaken concerning tourism and resilience from a network governance point of view. We analyze tourism supply chain networks with regard to resilience to climate change at the municipal governance scale of three Alpine villages. We compare these with a planned destination management organization (DMO as a governance entity of the same three municipalities on the regional scale. Network measures are analyzed via a quantitative social network analysis (SNA focusing on resilience from a tourism governance point of view. Results indicate higher resilience of the regional DMO because of a more flexible and diverse governance structure, more centralized steering of fast collective action, and improved innovative capacity, because of higher modularity and better core-periphery integration. Interpretations of quantitative results have been qualitatively validated by interviews and a workshop. We conclude that adaptation of tourism-dependent municipalities to gradual climate change should be dealt with at a regional governance scale and adaptation to sudden changes at a municipal scale. Overall, DMO building at a regional scale may enhance the resilience of tourism destinations, if the municipalities are well integrated.

  5. Integrative analysis of kinase networks in TRAIL-induced apoptosis provides a source of potential targets for combination therapy

    DEFF Research Database (Denmark)

    So, Jonathan; Pasculescu, Adrian; Dai, Anna Y.

    2015-01-01

    phosphoproteomics. With these protein interaction maps, we modeled information flow through the networks and identified apoptosis-modifying kinases that are highly connected to regulated substrates downstream of TRAIL. The results of this analysis provide a resource of potential targets for the development of TRAIL...

  6. SWI/SNF-like chromatin remodeling factor Fun30 supports point centromere function in S. cerevisiae.

    Directory of Open Access Journals (Sweden)

    Mickaël Durand-Dubief

    2012-09-01

    Full Text Available Budding yeast centromeres are sequence-defined point centromeres and are, unlike in many other organisms, not embedded in heterochromatin. Here we show that Fun30, a poorly understood SWI/SNF-like chromatin remodeling factor conserved in humans, promotes point centromere function through the formation of correct chromatin architecture at centromeres. Our determination of the genome-wide binding and nucleosome positioning properties of Fun30 shows that this enzyme is consistently enriched over centromeres and that a majority of CENs show Fun30-dependent changes in flanking nucleosome position and/or CEN core micrococcal nuclease accessibility. Fun30 deletion leads to defects in histone variant Htz1 occupancy genome-wide, including at and around most centromeres. FUN30 genetically interacts with CSE4, coding for the centromere-specific variant of histone H3, and counteracts the detrimental effect of transcription through centromeres on chromosome segregation and suppresses transcriptional noise over centromere CEN3. Previous work has shown a requirement for fission yeast and mammalian homologs of Fun30 in heterochromatin assembly. As centromeres in budding yeast are not embedded in heterochromatin, our findings indicate a direct role of Fun30 in centromere chromatin by promoting correct chromatin architecture.

  7. Combined effect of CVR and penetration of DG in the voltage profile and losses of lowvoltage secondary distribution networks

    Science.gov (United States)

    Bokhari, Abdullah

    Demarcations between traditional distribution power systems and distributed generation (DG) architectures are increasingly evolving as higher DG penetration is introduced in the system. The concerns in existing electric power systems (EPSs) to accommodate less restrictive interconnection policies while maintaining reliability and performance of power delivery have been the major challenge for DG growth. In this dissertation, the work is aimed to study power quality, energy saving and losses in a low voltage distributed network under various DG penetration cases. Simulation platform suite that includes electric power system, distributed generation and ZIP load models is implemented to determine the impact of DGs on power system steady state performance and the voltage profile of the customers/loads in the network under the voltage reduction events. The investigation designed to test the DG impact on power system starting with one type of DG, then moves on multiple DG types distributed in a random case and realistic/balanced case. The functionality of the proposed DG interconnection is designed to meet the basic requirements imposed by the various interconnection standards, most notably IEEE 1547, public service commission, and local utility regulation. It is found that implementation of DGs on the low voltage secondary network would improve customer's voltage profile, system losses and significantly provide energy savings and economics for utilities. In a network populated with DGs, utility would have a uniform voltage profile at the customers end as the voltage profile becomes more concentrated around targeted voltage level. The study further reinforced the concept that the behavior of DG in distributed network would improve voltage regulation as certain percentage reduction on utility side would ensure uniform percentage reduction seen by all customers and reduce number of voltage violations.

  8. Interview with Alison Bechdel about her presentation of Fun Home in Paris and Tours

    Directory of Open Access Journals (Sweden)

    Anne Crémieux

    2007-09-01

    Full Text Available “Self-portrait by Alison Bechdel,” Courtesy of the authorTransat: How has Fun Home’s reception been different in nature from the reactions to Dykes to Watch Out For? Alison Bechdel: Fun Home has had a very different reception than Dykes to Watch Out For. It’s a very different type of book. I don’t want to downplay DTWOF—I’m very proud of the series, and I think it’s been a worthy contribution to queer culture as well as to the comics genre. But Fun Home was a real creative leap for me. Creati...

  9. Network Simulation solution of free convective flow from a vertical cone with combined effect of non- uniform surface heat flux and heat generation or absorption

    Science.gov (United States)

    Immanuel, Y.; Pullepu, Bapuji; Sambath, P.

    2018-04-01

    A two dimensional mathematical model is formulated for the transitive laminar free convective, incompressible viscous fluid flow over vertical cone with variable surface heat flux combined with the effects of heat generation and absorption is considered . using a powerful computational method based on thermoelectric analogy called Network Simulation Method (NSM0, the solutions of governing nondimensionl coupled, unsteady and nonlinear partial differential conservation equations of the flow that are obtained. The numerical technique is always stable and convergent which establish high efficiency and accuracy by employing network simulator computer code Pspice. The effects of velocity and temperature profiles have been analyzed for various factors, namely Prandtl number Pr, heat flux power law exponent n and heat generation/absorption parameter Δ are analyzed graphically.

  10. Mobilidade de cátions e correção da acidez de um Cambissolo em função da aplicação superficial de calcário combinado com sais de potássio Cation mobility and acidity decrease in a Haplumbrept due to surface liming combined with potassium fertilizers

    Directory of Open Access Journals (Sweden)

    Lisandra Pinto Della Flora

    2007-12-01

    low solubility, to the increase in soil negative charge in the applied zones, and to the short permanence of anions of added anions in the soil solution. This study was carried out to evaluate the effect of anions added as potassium salts on increasing the reactivity of surface-applied limestone. The experiment was carried out in 2005 on a Haplumbrept (360 g kg-1 clay, 60 g kg-1 organic matter, and pH 4.1. Three rates of dolomitic lime (0, 0.74 and 1.48 kg m-2 were combined or not with 40 g m-2 K as KCl or KNO3, all mixed with the top one centimeter of the soil. The experimental units (10 x 30 cm PVC columns containing 1.5 kg soil were percolated 21 times at weekly intervals with 300 mL distilled water, totalizing a volume equivalent to 800 mm rain. Potassium salts leached much more Ca and Mg than lime. Averaged across liming treatments, the salts increased total leaching from 36 - 136 mg for Ca, 5.8 - 26 mg for Mg, and 25 - 51 mg/column for K compared to the treatment without salts. In the absence of salts, the highest limestone rate resulted in leaching of only 5 mg Ca and 1.2 mg/column of Mg. Surface liming affected soil pH and exchangeable Ca, Mg and Al down to a maximum depth of 5.0 cm. These soil modifications were almost always proportional to the applied dose, but were not influenced by K salts. Potassium fertilizers had no influence on the reactivity of surface liming.

  11. High-throughput profiling of signaling networks identifies mechanism-based combination therapy to eliminate microenvironmental resistance in acute myeloid leukemia.

    Science.gov (United States)

    Zeng, Zhihong; Liu, Wenbin; Tsao, Twee; Qiu, YiHua; Zhao, Yang; Samudio, Ismael; Sarbassov, Dos D; Kornblau, Steven M; Baggerly, Keith A; Kantarjian, Hagop M; Konopleva, Marina; Andreeff, Michael

    2017-09-01

    The bone marrow microenvironment is known to provide a survival advantage to residual acute myeloid leukemia cells, possibly contributing to disease recurrence. The mechanisms by which stroma in the microenvironment regulates leukemia survival remain largely unknown. Using reverse-phase protein array technology, we profiled 53 key protein molecules in 11 signaling pathways in 20 primary acute myeloid leukemia samples and two cell lines, aiming to understand stroma-mediated signaling modulation in response to the targeted agents temsirolimus (MTOR), ABT737 (BCL2/BCL-XL), and Nutlin-3a (MDM2), and to identify the effective combination therapy targeting acute myeloid leukemia in the context of the leukemia microenvironment. Stroma reprogrammed signaling networks and modified the sensitivity of acute myeloid leukemia samples to all three targeted inhibitors. Stroma activated AKT at Ser473 in the majority of samples treated with single-agent ABT737 or Nutlin-3a. This survival mechanism was partially abrogated by concomitant treatment with temsirolimus plus ABT737 or Nutlin-3a. Mapping the signaling networks revealed that combinations of two inhibitors increased the number of affected proteins in the targeted pathways and in multiple parallel signaling, translating into facilitated cell death. These results demonstrated that a mechanism-based selection of combined inhibitors can be used to guide clinical drug selection and tailor treatment regimens to eliminate microenvironment-mediated resistance in acute myeloid leukemia. Copyright© 2017 Ferrata Storti Foundation.

  12. Determination of Elastic and Dissipative Properties of Material Using Combination of FEM and Complex Artificial Neural Networks

    Science.gov (United States)

    Soloviev, A. N.; Giang, N. D. T.; Chang, S.-H.

    This paper describes the application of complex artificial neural networks (CANN) in the inverse identification problem of the elastic and dissipative properties of solids. Additional information for the inverse problem serves the components of the displacement vector measured on the body boundary, which performs harmonic oscillations at the first resonant frequency. The process of displacement measurement in this paper is simulated using calculation of finite element (FE) software ANSYS. In the shown numerical example, we focus on the accurate identification of elastic modulus and quality of material depending on the number of measurement points and their locations as well as on the architecture of neural network and time of the training process, which is conducted by using algorithms RProp, QuickProp.

  13. A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity

    OpenAIRE

    Frost, William N.; Wang, Jean; Brandon, Christopher J.

    2007-01-01

    Optical recording studies of invertebrate neural networks with voltage-sensitive dyes seldom employ conventional intracellular electrodes. This may in part be due to the traditional reliance on compound microscopes for such work. While such microscopes have high light-gathering power, they do not provide depth of field, making working with sharp electrodes difficult. Here we describe a hybrid microscope design, with switchable compound and stereo objectives, that eases the use of conventional...

  14. Combined Rate and Power Allocation with Link Scheduling in Wireless Data Packet Relay Networks with Fading Channels

    OpenAIRE

    Subhrakanti Dey; Minyi Huang

    2007-01-01

    We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal ...

  15. IN MY OPINION: Physics is fun - for whom?

    Science.gov (United States)

    Allday, Jonathan

    1998-09-01

    (modified) Punch cartoon. Marcie and Linus are discussing life: Marcie `Thank you for the Chocolate Sundae, Linus' Linus `You're welcome... Maybe we can do it again sometime?' Marcie `I don't think so... I don't find you very interesting.' Linus, wistfully and leaning against a tree - `Physics....' This cartoon the students find funny. The fact that the study of physics should be a block to a meaningful relationship seems to strike a chord with them. It takes them by surprise that physicists have a real life. Now I realize that any teacher having a real life often takes students by surprise. I remember visiting my mother's infants school when I was a sixth-former and the kids there found it unbelievable that Mrs Allday should have a son. Teachers, you see, cease to exist the minute the students walk out of the classroom. However, physics and its practitioners seem to be especially branded in this way. From time to time I show videos to my students. Well chosen ones (so I think) that reflect modern developments and show physicists enjoying what they are doing. One such tape shows the reaction to the first pictures coming down from the newly repaired Hubble Space Telescope. The control room is filled with whoops, delighted cheering and general bouncing up and down with enthusiasm. This always raises a laugh. However, one can tell that they are being laughed at, not with. Another tape is about the comet strike on Jupiter. The narrator spends some time talking with Gene and Carolyn Shoemaker (two of the discoverers of the comet) - a married team of astronomers. You can see that their married life in part revolves round their joint love of astronomy and physics. I have overheard comments like `can you imagine the breakfast conversations?' Why do students find it so difficult to imagine that physicists in real life have fun doing physics? Pondering this I have come to the conclusion that they do not see enough teachers having fun teaching the subject. Perhaps with all the time we

  16. Frequency of Victimization Experiences and Well-Being Among Online, Offline, and Combined Victims on Social Online Network Sites of German Children and Adolescents.

    Science.gov (United States)

    Glüer, Michael; Lohaus, Arnold

    2015-01-01

    Victimization is associated with negative developmental outcomes in childhood and adolescence. However, previous studies have provided mixed results regarding the association between offline and online victimization and indicators of social, psychological, and somatic well-being. In this study, we investigated 1,890 German children and adolescents (grades 5-10, mean age = 13.9; SD = 2.1) with and without offline or online victimization experiences who participated in a social online network (SNS). Online questionnaires were used to assess previous victimization (offline, online, combined, and without), somatic and psychological symptoms, self-esteem, and social self-concept (social competence, resistance to peer influence, esteem by others). In total, 1,362 (72.1%) children and adolescents reported being a member of at least one SNS, and 377 students (28.8%) reported previous victimization. Most children and adolescents had offline victimization experiences (17.5%), whereas 2.7% reported online victimization, and 8.6% reported combined experiences. Girls reported more online and combined victimization, and boys reported more offline victimization. The type of victimization (offline, online, combined) was associated with increased reports of psychological and somatic symptoms, lower self-esteem and esteem by others, and lower resistance to peer influences. The effects were comparable for the groups with offline and online victimization. They were, however, increased in the combined group in comparison to victims with offline experiences alone.

  17. Classification of protein fold classes by knot theory and prediction of folds by neural networks: A combined theoretical and experimental approach

    DEFF Research Database (Denmark)

    Ramnarayan, K.; Bohr, Henrik; Jalkanen, Karl J.

    2008-01-01

    We present different means of classifying protein structure. One is made rigorous by mathematical knot invariants that coincide reasonably well with ordinary graphical fold classification and another classification is by packing analysis. Furthermore when constructing our mathematical fold...... classifications, we utilize standard neural network methods for predicting protein fold classes from amino acid sequences. We also make an analysis of the redundancy of the structural classifications in relation to function and ligand binding. Finally we advocate the use of combining the measurement of the VA...

  18. How "fun/importance" fit affects performance: relating implicit theories to instructions.

    Science.gov (United States)

    Bianco, Amy T; Higgins, E Tory; Klem, Adena

    2003-09-01

    People experience a regulatory fit when they employ means of goal pursuit that fit their regulatory orientation, and this fit increases motivation that can enhance performance. The present studies extend previous research on regulatory fit to the classic motivational variables of fun and importance. They also examine for the first time the effect on performance of the fit between individuals' implicit theories about a task's fun or importance and their strategic engagement of the task as fun or important as induced by task instructions. In all three studies, task performance was better when the external task instructions "fit" rather than did not fit participants' implicit theory for the task. The implications of these findings for understanding the motivational effects of fun and importance are discussed.

  19. Disentangling Fun and Enjoyment in Exergames Using an Expanded Design, Play, Experience Framework: A Narrative Review.

    Science.gov (United States)

    Mellecker, Robin; Lyons, Elizabeth J; Baranowski, Tom

    2013-06-01

    With exergames (as with physical activity in general), more intense and longer-duration game play should accrue more health benefits. Exergames, however, appear to be played for relatively short durations, often at medium or lower intensities. Ostensibly games are played for fun or enjoyment. Enhancing the fun or enjoyment experienced during exergame play should enhance the intensity and duration of physical activity, and thereby the health benefits. Research, reviewed herein, indicates fun and/or enjoyment in games are inherently laden with psychosocial, physiological, and embodiment substrates. Physical activity may also have separate or closely related psychosocial, physiological, and embodiment enjoyment substrates. Research is needed to integrate these levels of experience and to identify the game mechanics that enhance, and even maximize, the fun or enjoyment experienced in exergames, to thereby increase the health benefit.

  20. Make Celebrations Fun, Healthy, and Active: 10 Tips to Creating Healthy, Active Events

    Science.gov (United States)

    United States Department of Agriculture 10 tips Nutrition Education Series MyPlate MyWins Based on the Dietary Guidelines for Americans Make celebrations fun, healthy, and active Eating healthy and being physically active can be a ...

  1. A New Architecture for FUN3D on Modern HPC Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The goal of this project is to refactor NASA's FUN3D computation fluid dynamic (CFD) simulation code to enable it to take full advantage of accelerator hardware...

  2. A Limited Evaluation of Full Scale Control Surface Deflection Drag (Have FUN)

    National Research Council Canada - National Science Library

    Reinhardt, R. B; Celi, Sean A; Geraghty, Jeffrey T; Stahl, James W; Glover, Victor J; Bowman, Geoffrey G

    2007-01-01

    The Have FUN (FUll Scale Numbers) Test Management Project was conducted at the request of the USAF TPS as an investigation into the drag caused by control surface deflection during dynamic soaring techniques...

  3. “Pick-up Lines”: A Fun Way to Facilitate Learning Microbiological Concepts

    Directory of Open Access Journals (Sweden)

    Thomas Edison E. dela Cruz

    2014-05-01

    Full Text Available Learning microbiology can be made fun by writing funny lines related to microbiology. Students were tasked to create their own pick-up lines and explain these based on their understanding of the basic concepts in microbiology.

  4. Olympic opening ceremony was a vibrant feast of fun and energy.

    Science.gov (United States)

    Crawford, Linda

    2012-08-08

    If director Danny Boyle's intention at the Olympic opening ceremony was to provide a snapshot of Britain today, he succeeded. It was an inspired feast of energy, colour and vibrancy - as well as being great fun.

  5. Hybrid dynamic modeling of Escherichia coli central metabolic network combining Michaelis–Menten and approximate kinetic equations

    DEFF Research Database (Denmark)

    Costa, Rafael S.; Machado, Daniel; Rocha, Isabel

    2010-01-01

    , represent nowadays the limiting factor in the construction of such models. In this study, we compare four alternative modeling approaches based on Michaelis–Menten kinetics for the bi-molecular reactions and different types of simplified rate equations for the remaining reactions (generalized mass action......The construction of dynamic metabolic models at reaction network level requires the use of mechanistic enzymatic rate equations that comprise a large number of parameters. The lack of knowledge on these equations and the difficulty in the experimental identification of their associated parameters...

  6. Combining ground-based and airborne EM through Artificial Neural Networks for modelling glacial till under saline groundwater conditions

    DEFF Research Database (Denmark)

    Gunnink, J.L.; Bosch, A.; Siemon, B.

    2012-01-01

    Airborne electromagnetic (AEM) methods supply data over large areas in a cost-effective way. We used ArtificialNeural Networks (ANN) to classify the geophysical signal into a meaningful geological parameter. By using examples of known relations between ground-based geophysical data (in this case...... electrical conductivity, EC, from electrical cone penetration tests) and geological parameters (presence of glacial till), we extracted learning rules that could be applied to map the presence of a glacial till using the EC profiles from the airborne EM data. The saline groundwater in the area was obscuring...

  7. Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network.

    Science.gov (United States)

    Salehpour, Mehdi; Behrad, Alireza

    2017-10-01

    This study proposes a new algorithm for nonrigid coregistration of synthetic aperture radar (SAR) and optical images. The proposed algorithm employs point features extracted by the binary robust invariant scalable keypoints algorithm and a new method called weighted bidirectional matching for initial correspondence. To refine false matches, we assume that the transformation between SAR and optical images is locally rigid. This property is used to refine false matches by assigning scores to matched pairs and clustering local rigid transformations using a two-layer Kohonen network. Finally, the thin plate spline algorithm and mutual information are used for nonrigid coregistration of SAR and optical images.

  8. Six to Ten Digits Multiplication Fun Learning Using Puppet Prototype

    Science.gov (United States)

    Islamiah Rosli, D.'oria; Ali, Azita; Peng, Lim Soo; Sujardi, Imam; Usodo, Budi; Adie Perdana, Fengky

    2017-01-01

    Logic and technical subjects require students to understand basic knowledge in mathematic. For instance, addition, minus, division and multiplication operations need to be mastered by students due to mathematic complexity as the learning mathematic grows higher. Weak foundation in mathematic also contribute to high failure rate in mathematic subjects in schools. In fact, students in primary schools are struggling to learn mathematic because they need to memorize formulas, multiplication or division operations. To date, this study will develop a puppet prototyping for learning mathematic for six to ten digits multiplication. Ten participants involved in the process of developing the prototype in this study. Students involved in the study were those from the intermediate class students whilst teachers were selected based on their vast knowledge and experiences and have more than five years of experience in teaching mathematic. Close participatory analysis will be used in the prototyping process as to fulfil the requirements of the students and teachers whom will use the puppet in learning six to ten digit multiplication in mathematic. Findings showed that, the students had a great time and fun learning experience in learning multiplication and they able to understand the concept of multiplication using puppet. Colour and materials of the puppet also help to attract student attention during learning. Additionally, students able to visualized and able to calculate accurate multiplication value and the puppet help them to recall in multiplying and adding the digits accordingly.

  9. Is talking to an automated teller machine natural and fun?

    Science.gov (United States)

    Chan, F Y; Khalid, H M

    Usability and affective issues of using automatic speech recognition technology to interact with an automated teller machine (ATM) are investigated in two experiments. The first uncovered dialogue patterns of ATM users for the purpose of designing the user interface for a simulated speech ATM system. Applying the Wizard-of-Oz methodology, multiple mapping and word spotting techniques, the speech driven ATM accommodates bilingual users of Bahasa Melayu and English. The second experiment evaluates the usability of a hybrid speech ATM, comparing it with a simulated manual ATM. The aim is to investigate how natural and fun can talking to a speech ATM be for these first-time users. Subjects performed the withdrawal and balance enquiry tasks. The ANOVA was performed on the usability and affective data. The results showed significant differences between systems in the ability to complete the tasks as well as in transaction errors. Performance was measured on the time taken by subjects to complete the task and the number of speech recognition errors that occurred. On the basis of user emotions, it can be said that the hybrid speech system enabled pleasurable interaction. Despite the limitations of speech recognition technology, users are set to talk to the ATM when it becomes available for public use.

  10. Learning through a Game - Exploring Fun and Learning in a Project Management Game

    OpenAIRE

    Hansen, Daniel Sollie; Storjord, David

    2016-01-01

    The goal of this thesis is to explore the teaching capabilities of games by motivating players through fun. We do this by first exploring perspectives of fun and learning in games; project management concepts and previous games. From these findings we implement our own game prototype where the player learns project management concepts simultaneously as they learn the game. This prototype is then evaluated through a number of experiments. Finally we discuss the results of the experiments and c...

  11. Work or Fun? How Task Construal and Completion Influence Regulatory Behavior

    OpenAIRE

    Juliano Laran; Chris Janiszewski

    2011-01-01

    Volitional behaviors can be construed as "work" (extrinsically motivated) or as "fun" (intrinsically motivated). When volitional behaviors are construed as an obligation to work, completing the behavior depletes a consumer, and subsequent self-control becomes more difficult. When volitional behaviors are construed as an opportunity to have fun, completing the behavior vitalizes a consumer, and subsequent self-control becomes easier. Six studies show how individual differences and contextual f...

  12. Comparison of strategies for combining dynamic linear models with artificial neural networks for detecting diarrhea in slaughter pigs

    DEFF Research Database (Denmark)

    Jensen, Dan Børge; Kristensen, Anders Ringgaard

    2016-01-01

    The drinking behavior of healthy pigs is known to follow predictable diurnal patterns, and these patterns are further known to change in relation to undesired events such as diarrhea. We therefore expect that automatic monitoring of slaughter pig drinking behavior, combined with machine learning...

  13. Combining an Elastic Network With a Coarse-Grained Molecular Force Field : Structure, Dynamics, and Intermolecular Recognition

    NARCIS (Netherlands)

    Periole, Xavier; Cavalli, Marco; Marrink, Siewert-Jan; Ceruso, Marco A.

    Structure-based and physics-based coarse-grained molecular force fields have become attractive approaches to gain mechanistic insight into the function of large biomolecular assemblies. Here, we study how both approaches can be combined into a single representation, that we term ELNEDIN. In this

  14. Fun During Knee Rehabilitation: Feasibility and Acceptability Testing of a New Android-Based Training Device.

    Science.gov (United States)

    Weber-Spickschen, Thomas Sanjay; Colcuc, Christian; Hanke, Alexander; Clausen, Jan-Dierk; James, Paul Abraham; Horstmann, Hauke

    2017-01-01

    The initial goals of rehabilitation after knee injuries and operations are to achieve full knee extension and to activate quadriceps muscle. In addition to regular physiotherapy, an android-based knee training device is designed to help patients achieve these goals and improve compliance in the early rehabilitation period. This knee training device combines fun in a computer game with muscular training or rehabilitation. Our aim was to test the feasibility and acceptability of this new device. 50 volunteered subjects enrolled to test out the computer game aided device. The first game was the high-striker game, which recorded maximum knee extension power. The second game involved controlling quadriceps muscular power to simulate flying an aeroplane in order to record accuracy of muscle activation. The subjects evaluated this game by completing a simple questionnaire. No technical problem was encountered during the usage of this device. No subjects complained of any discomfort after using this device. Measurements including maximum knee extension power, knee muscle activation and control were recorded successfully. Subjects rated their experience with the device as either excellent or very good and agreed that the device can motivate and monitor the progress of knee rehabilitation training. To the best of our knowledge, this is the first android-based tool available to fast track knee rehabilitation training. All subjects gave very positive feedback to this computer game aided knee device.

  15. Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network

    Science.gov (United States)

    Khajeh, M.; Pourkarami, A.; Arefnejad, E.; Bohlooli, M.; Khatibi, A.; Ghaffari-Moghaddam, M.; Zareian-Jahromi, S.

    2017-09-01

    Chitosan-zinc oxide nanoparticles (CZPs) were developed for solid-phase extraction. Combined artificial neural network-ant colony optimization (ANN-ACO) was used for the simultaneous preconcentration and determination of lead (Pb2+) ions in water samples prior to graphite furnace atomic absorption spectrometry (GF AAS). The solution pH, mass of adsorbent CZPs, amount of 1-(2-pyridylazo)-2-naphthol (PAN), which was used as a complexing agent, eluent volume, eluent concentration, and flow rates of sample and eluent were used as input parameters of the ANN model, and the percentage of extracted Pb2+ ions was used as the output variable of the model. A multilayer perception network with a back-propagation learning algorithm was used to fit the experimental data. The optimum conditions were obtained based on the ACO. Under the optimized conditions, the limit of detection for Pb2+ ions was found to be 0.078 μg/L. This procedure was also successfully used to determine the amounts of Pb2+ ions in various natural water samples.

  16. Distribution and Network of Basal Temporal Language Areas: A Study of the Combination of Electric Cortical Stimulation and Diffusion Tensor Imaging.

    Science.gov (United States)

    Enatsu, Rei; Kanno, Aya; Ookawa, Satoshi; Ochi, Satoko; Ishiai, Sumio; Nagamine, Takashi; Mikuni, Nobuhiro

    2017-10-01

    The basal temporal language area (BTLA) is considered to have several functions in language processing; however, its brain network is still unknown. This study investigated the distribution and networks of the BTLA using a combination of electric cortical stimulation and diffusion tensor imaging (DTI). 10 patients with intractable focal epilepsy who underwent presurgical evaluation with subdural electrodes were enrolled in this study (language dominant side: 6 patients, language nondominant side: 4 patients). Electric stimulation at 50 Hz was applied to the electrodes during Japanese sentence reading, morphograms (kanji) reading, and syllabograms (kana) reading tasks to identify the BTLA. DTI was used to identify the subcortical fibers originating from the BTLA found by electric stimulation. The BTLA was found in 6 patients who underwent implantation of the subdural electrodes in the dominant hemisphere. The BTLA was located anywhere between 20 mm and 56 mm posterior to the temporal tips. In 3 patients, electric stimulation of some or all areas within the BTLA induced disturbance in reading of kanji words only. DTI detected the inferior longitudinal fasciculus (ILF) in all patients and the uncinate fasciculus (UF) in 1 patient, originating from the BTLA. ILF was detected from both kanji-specific areas and kanji-nonspecific areas. This study indicates that the network of the BTLA is a part of a ventral stream and is mainly composed of the ILF, which acts as a critical structure for lexical retrieval. ILF is also associated with the specific processing of kanji words. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews.

    Science.gov (United States)

    Tutubalina, Elena; Nikolenko, Sergey

    2017-01-01

    Adverse drug reactions (ADRs) are an essential part of the analysis of drug use, measuring drug use benefits, and making policy decisions. Traditional channels for identifying ADRs are reliable but very slow and only produce a small amount of data. Text reviews, either on specialized web sites or in general-purpose social networks, may lead to a data source of unprecedented size, but identifying ADRs in free-form text is a challenging natural language processing problem. In this work, we propose a novel model for this problem, uniting recurrent neural architectures and conditional random fields. We evaluate our model with a comprehensive experimental study, showing improvements over state-of-the-art methods of ADR extraction.

  18. Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews

    Directory of Open Access Journals (Sweden)

    Elena Tutubalina

    2017-01-01

    Full Text Available Adverse drug reactions (ADRs are an essential part of the analysis of drug use, measuring drug use benefits, and making policy decisions. Traditional channels for identifying ADRs are reliable but very slow and only produce a small amount of data. Text reviews, either on specialized web sites or in general-purpose social networks, may lead to a data source of unprecedented size, but identifying ADRs in free-form text is a challenging natural language processing problem. In this work, we propose a novel model for this problem, uniting recurrent neural architectures and conditional random fields. We evaluate our model with a comprehensive experimental study, showing improvements over state-of-the-art methods of ADR extraction.

  19. Combined wavelet transform-artificial neural network use in tablet active content determination by near-infrared spectroscopy.

    Science.gov (United States)

    Chalus, Pascal; Walter, Serge; Ulmschneider, Michel

    2007-05-22

    The pharmaceutical industry faces increasing regulatory pressure to optimize quality control. Content uniformity is a basic release test for solid dosage forms. To accelerate test throughput and comply with the Food and Drug Administration's process analytical technology initiative, attention is increasingly turning to nondestructive spectroscopic techniques, notably near-infrared (NIR) spectroscopy (NIRS). However, validation of NIRS using requisite linearity and standard error of prediction (SEP) criteria remains a challenge. This study applied wavelet transformation of the NIR spectra of a commercial tablet to build a model using conventional partial least squares (PLS) regression and an artificial neural network (ANN). Wavelet coefficients in the PLS and ANN models reduced SEP by up to 60% compared to PLS models using mathematical spectra pretreatment. ANN modeling yielded high-linearity calibration and a correlation coefficient exceeding 0.996.

  20. Combined Rate and Power Allocation with Link Scheduling in Wireless Data Packet Relay Networks with Fading Channels

    Directory of Open Access Journals (Sweden)

    Subhrakanti Dey

    2007-08-01

    Full Text Available We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal power, rate, and transmission time allocation at the wireless links. We further consider an optimal power allocation problem for multiple transmitting sources in the same framework. Performances of the resource allocation algorithms including the effect of buffer load control are illustrated via extensive simulation studies.

  1. Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Panda, Priyadarshini; Roy, Kaushik

    2017-01-01

    Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

  2. Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.

    Science.gov (United States)

    McAllister, Patrick; Zheng, Huiru; Bond, Raymond; Moorhead, Anne

    2018-04-01

    Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and manage obesity. Computer vision methods have been applied to food logging to automate image classification for monitoring dietary intake. In this work we applied pretrained ResNet-152 and GoogleNet convolutional neural networks (CNNs), initially trained using ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset with MatConvNet package, to extract features from food image datasets; Food 5K, Food-11, RawFooT-DB, and Food-101. Deep features were extracted from CNNs and used to train machine learning classifiers including artificial neural network (ANN), support vector machine (SVM), Random Forest, and Naive Bayes. Results show that using ResNet-152 deep features with SVM with RBF kernel can accurately detect food items with 99.4% accuracy using Food-5K validation food image dataset and 98.8% with Food-5K evaluation dataset using ANN, SVM-RBF, and Random Forest classifiers. Trained with ResNet-152 features, ANN can achieve 91.34%, 99.28% when applied to Food-11 and RawFooT-DB food image datasets respectively and SVM with RBF kernel can achieve 64.98% with Food-101 image dataset. From this research it is clear that using deep CNN features can be used efficiently for diverse food item image classification. The work presented in this research shows that pretrained ResNet-152 features provide sufficient generalisation power when applied to a range of food image classification tasks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Wireless home networking for dummies

    CERN Document Server

    Briere, Danny; Ferris, Edward

    2010-01-01

    The perennial bestseller shows you how share your files and Internet connection across a wireless network. Fully updated for Windows 7 and Mac OS X Snow Leopard, this new edition of this bestseller returns with all the latest in wireless standards and security. This fun and friendly guide shows you how to integrate your iPhone, iPod touch, smartphone, or gaming system into your home network. Veteran authors escort you through the various financial and logisitical considerations that you need to take into account before building a wireless network at home.: Covers the basics of planning, instal

  4. Fun Teaching: The Key to the Future Climatology

    Science.gov (United States)

    Mulvey, G.

    2016-12-01

    In general meteorology is a science of immediate impact. What will the weather be tomorrow or next week? Climatology and climate change is the science of our long range past and future. Decisions made in the past, now, and in the future on climate change issues did and will continue to impact the global climate. It is essential that current and future generations understand the causes of climate change to make informed decisions regarding individual and government actions needed to mitigate human impacts on the future climate. The university challenge is make climatology an exciting and dynamic adventure into the past, present and future. Instructor and supporting organizations have stepped outside the "old yellow notes" approach to enable students to progress beyond remember, understand, and apply; to analyze, evaluate and create. Responding to this instructional challenge by shifting instructional techniques and tools to a new paradigm does not happen overnight. The instructional strategies to make this jump are known in general, but not in specific. This paper deals with examples of how to translate the instructional strategies into practice in ways that are fun for students and instructors. Techniques to be described include interactive discussions, debates and team challenges, such as: - Describing continental climates during past geological periods - In-class teams debates on legislature to control/modify human CO2 releases Low or no cost teaching aids such as video clips, demonstrations, specimens, and experiments will be described with outcomes and resources interest. Some examples to be discussed are - Tree cookies, cross sections - Ocean core smear slide samples of diatoms, foraminifera, etc. - Ice pack/glacial melt experiments - Glacial flow and interpreting glacial ice cores experiment - Field trips to observe geological strata and geological samples - Storytelling - the shared experiences of each instructor

  5. Neural correlates and network connectivity underlying narrative production and comprehension: a combined fMRI and PET study.

    Science.gov (United States)

    AbdulSabur, Nuria Y; Xu, Yisheng; Liu, Siyuan; Chow, Ho Ming; Baxter, Miranda; Carson, Jessica; Braun, Allen R

    2014-08-01

    The neural correlates of narrative production and comprehension remain poorly understood. Here, using positron emission tomography (PET), functional magnetic resonance imaging (fMRI), contrast and functional network connectivity analyses we comprehensively characterize the neural mechanisms underlying these complex behaviors. Eighteen healthy subjects told and listened to fictional stories during scanning. In addition to traditional language areas (e.g., left inferior frontal and posterior middle temporal gyri), both narrative production and comprehension engaged regions associated with mentalizing and situation model construction (e.g., dorsomedial prefrontal cortex, precuneus and inferior parietal lobules) as well as neocortical premotor areas, such as the pre-supplementary motor area and left dorsal premotor cortex. Narrative comprehension alone showed marked bilaterality, activating right hemisphere homologs of perisylvian language areas. Narrative production remained predominantly left lateralized, uniquely activating executive and motor-related regions essential to language formulation and articulation. Connectivity analyses revealed strong associations between language areas and the superior and middle temporal gyri during both tasks. However, only during storytelling were these same language-related regions connected to cortical and subcortical motor regions. In contrast, during story comprehension alone, they were strongly linked to regions supporting mentalizing. Thus, when employed in a more complex, ecologically-valid context, language production and comprehension show both overlapping and idiosyncratic patterns of activation and functional connectivity. Importantly, in each case the language system is integrated with regions that support other cognitive and sensorimotor domains. Copyright © 2014. Published by Elsevier Ltd.

  6. A combined neural network and mechanistic approach for the prediction of corrosion rate and yield strength of magnesium-rare earth alloys

    Energy Technology Data Exchange (ETDEWEB)

    Birbilis, N., E-mail: nick.birbilis@monash.ed [ARC Centre of Excellence for Design in Light Metals, Monash University (Australia); CAST Co-operative Research Centre, Monash University (Australia); Cavanaugh, M.K. [Department of Materials Science and Engineering, The Ohio State University (United States); Sudholz, A.D. [ARC Centre of Excellence for Design in Light Metals, Monash University (Australia); Zhu, S.M.; Easton, M.A. [CAST Co-operative Research Centre, Monash University (Australia); Gibson, M.A. [CSIRO Division of Process Science and Engineering (Australia)

    2011-01-15

    Research highlights: This study presents a body of corrosion data for a set of custom alloys and displays this in multivariable space. These alloys represent the next generation of Mg alloys for auto applications. The data is processed using an ANN model, which makes it possible to yield a single expression for prediction of corrosion rate (and strength) as a function of any input composition (of Ce, La or Nd between 0 and 6 wt.%). The relative influence of the various RE elements on corrosion is assessed, with the outcome that Nd additions can offer comparable strength with minimal rise in corrosion rate. The morphology and solute present in the eutectic region itself (as opposed to just the intermetallic presence) was shown - for the first time - to also be a key contributor to corrosion. The above approach sets the foundation for rational alloy design of alloys with corrosion performance in mind. - Abstract: Additions of Ce, La and Nd to Mg were made in binary, ternary and quaternary combinations up to {approx}6 wt.%. This provided a dataset that was used in developing a neural network model for predicting corrosion rate and yield strength. Whilst yield strength increased with RE additions, corrosion rates also systematically increased, however, this depended on the type of RE element added and the combination of elements added (along with differences in intermetallic morphology). This work is permits an understanding of Mg-RE alloy performance, and can be exploited in Mg alloy design for predictable combinations of strength and corrosion resistance.

  7. Dissociating Memory Networks in Early Alzheimer’s Disease and Frontotemporal Lobar Degeneration - A Combined Study of Hypometabolism and Atrophy

    Science.gov (United States)

    Frisch, Stefan; Dukart, Juergen; Vogt, Barbara; Horstmann, Annette; Becker, Georg; Villringer, Arno; Barthel, Henryk; Sabri, Osama; Müller, Karsten; Schroeter, Matthias L.

    2013-01-01

    distributed networks which break down in brain degeneration. PMID:23457466

  8. Modeling metabolic networks in C. glutamicum: a comparison of rate laws in combination with various parameter optimization strategies

    Directory of Open Access Journals (Sweden)

    Oldiges Marco

    2009-01-01

    Full Text Available Abstract Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1 experimental measurement of participating molecules, (2 assignment of rate laws to each reaction, and (3 parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem. Results We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1 coarse-grained comparison of the algorithms on all models and (2 fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis. Conclusion A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics

  9. A Web 2.0 and Epidemiology Mash-Up: Using Respondent-Driven Sampling in Combination with Social Network Site Recruitment to Reach Young Transwomen.

    Science.gov (United States)

    Arayasirikul, Sean; Chen, Yea-Hung; Jin, Harry; Wilson, Erin

    2016-06-01

    Respondent-driven sampling (RDS) peer referral has been proven to be an effective recruitment method for hard-to-reach populations; however, its application in diverse populations is limited. Recruitment occurred in two phases: RDS-only followed by development and implementation of an online social network strategy in combination with RDS peer referral (RDS + SNS). Compared to RDS-only, RDS + SNS reached a sample that was younger (χ(2) = 9.19, P = .03), more likely to identify with a non-binary gender identity (χ(2) = 10.4247, P = .03), with less housing instability (50.5 vs. 68.6 %, χ(2) = 9.0038, P = .002) and less sex work (19.7 vs. 31.4 %, χ(2) = 5.0798, P = .02). Additionally, we describe lessons learned as a result of implementing our online social network strategy. Our findings underscore the importance of integrating Internet-driven strategies to meet challenges in sample diversity and recruitment of young transwomen.

  10. Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique

    International Nuclear Information System (INIS)

    Hou Zhijian; Lian Zhiwei; Yao Ye; Yuan Xinjian

    2006-01-01

    A novel method integrating rough sets (RS) theory and an artificial neural network (ANN) based on data-fusion technique is presented to forecast an air-conditioning load. Data-fusion technique is the process of combining multiple sensors data or related information to estimate or predict entity states. In this paper, RS theory is applied to find relevant factors to the load, which are used as inputs of an artificial neural-network to predict the cooling load. To improve the accuracy and enhance the robustness of load forecasting results, a general load-prediction model, by synthesizing multi-RSAN (MRAN), is presented so as to make full use of redundant information. The optimum principle is employed to deduce the weights of each RSAN model. Actual prediction results from a real air-conditioning system show that, the MRAN forecasting model is better than the individual RSAN and moving average (AMIMA) ones, whose relative error is within 4%. In addition, individual RSAN forecasting results are better than that of ARIMA

  11. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.

    Science.gov (United States)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.

  12. PDA-phone-based instant transmission of radiological images over a CDMA network by combining the PACS screen with a Bluetooth-interfaced local wireless link.

    Science.gov (United States)

    Kim, Dong Keun; Yoo, Sun K; Park, Jeong Jin; Kim, Sun Ho

    2007-06-01

    Remote teleconsultation by specialists is important for timely, correct, and specialized emergency surgical and medical decision making. In this paper, we designed a new personal digital assistant (PDA)-phone-based emergency teleradiology system by combining cellular communication with Bluetooth-interfaced local wireless links. The mobility and portability resulting from the use of PDAs and wireless communication can provide a more effective means of emergency teleconsultation without requiring the user to be limited to a fixed location. Moreover, it enables synchronized radiological image sharing between the attending physician in the emergency room and the remote specialist on picture archiving and communication system terminals without distorted image acquisition. To enable rapid and fine-quality radiological image transmission over a cellular network in a secure manner, progressive compression and security mechanisms have been incorporated. The proposed system is tested over a code division Multiple Access 1x-Evolution Data-Only network to evaluate the performance and to demonstrate the feasibility of this system in a real-world setting.

  13. Which are the best Chinese herbal injections combined with XELOX regimen for gastric cancer?: A PRISMA-compliant network meta-analysis.

    Science.gov (United States)

    Zhang, Dan; Wu, Jiarui; Wang, Kaihuan; Duan, Xiaojiao; Liu, Shi; Zhang, Bing

    2018-03-01

    The optimal Chinese herbal injections (CHIs) combined with XELOX regimen for patients with gastric cancer remains elusive. The aim of our network meta-analysis (NMA) is to explore the best options among different CHIs for gastric cancer. PubMed, Embase, the Cochrane Library, the China National Knowledge Infrastructure Database (CNKI), Wan-fang Database, Cqvip Database (VIP), China Biology Medicine disc (CBMdisc) were searched to identify RCTs which focused on CHIs against gastric cancer. The quality assessment of included randomized controlled trials (RCTs) was conducted by the Cochrane risk of bias tool. Standard pair-wise and Bayesian NMAs were performed to compare the efficacy and safety of different CHIs combined with the XELOX regimen via Stata 13.0 and WinBUGS1.4 software. A total of 2316 records were searched, the network of evidence included 26 eligible RCTs involving 13 types of CHIs and 2154 patients. The results suggested that Shenqifuzheng+ XELOX, Huachansu+ XELOX, Kangai+ XELOX, Javanica oil emulsion+ XELOX, Aidi injection+ XELOX might be the optimal treatment for gastric cancer in improving the performance status than using XELOX regimen single, with odds ratios (OR) and 95% confidence intervals (CIs) of 2.74 (1.24, 6.17), 8.27 (1.74, 42.43), 4.28 (1.80, 10.48), 5.14 (1.87, 16.28), 0.20 (0.090, 0.44). At the aspects of ADRs (adverse reactions), Compound Kushen+ XELOX, Lentinan+ XELOX, Xiaoaiping injection+ XELOX could obviously relieve leukopenia than only receiving XELOX regimen, and their ORs and 95% CIs were 5.62 (1.41, 36.24), 8.16 (2.25, 29.43), 5.69 (1.85, 15.77). Furthermore, Disodium cantharidinate and vitamin B6+ XELOX, Shenqifuzheng+ XELOX, Kangai+ XELOX, Lentinan+ XELOX could obviously relieve the nausea and vomiting than receiving the XELOX regimen alone, with ORs and 95% CIs of 5.29 (1.30, 23.96), 2.50 (1.16, 5.26), 2.42 (1.06, 5.63), 9.04 (3.24, 26.73). Nevertheless, CHIs combined with XELOX regimen did not confer higher better clinical

  14. Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks

    Science.gov (United States)

    Horita, Flávio E. A.; Albuquerque, João Porto de; Degrossi, Lívia C.; Mendiondo, Eduardo M.; Ueyama, Jó

    2015-07-01

    Effective flood risk management requires updated information to ensure that the correct decisions can be made. This can be provided by Wireless Sensor Networks (WSN) which are a low-cost means of collecting updated information about rivers. Another valuable resource is Volunteered Geographic Information (VGI) which is a comparatively new means of improving the coverage of monitored areas because it is able to supply supplementary information to the WSN and thus support decision-making in flood risk management. However, there still remains the problem of how to combine WSN data with VGI. In this paper, an attempt is made to investigate AGORA-DS, which is a Spatial Decision Support System (SDSS) that is able to make flood risk management more effective by combining these data sources, i.e. WSN with VGI. This approach is built over a conceptual model that complies with the interoperable standards laid down by the Open Geospatial Consortium (OGC) - e.g. Sensor Observation Service (SOS) and Web Feature Service (WFS) - and seeks to combine and present unified information in a web-based decision support tool. This work was deployed in a real scenario of flood risk management in the town of São Carlos in Brazil. The evidence obtained from this deployment confirmed that interoperable standards can support the integration of data from distinct data sources. In addition, they also show that VGI is able to provide information about areas of the river basin which lack data since there is no appropriate station in the area. Hence it provides a valuable support for the WSN data. It can thus be concluded that AGORA-DS is able to combine information provided by WSN and VGI, and provide useful information for supporting flood risk management.

  15. Suitability of the Miller Function and Participation Scales (M-FUN) for use with Israeli Children.

    Science.gov (United States)

    Rihtman, Tanya; Parush, Shula

    2014-01-01

    OBJECTIVE. Our aim was to generate a Hebrew translation of the Miller Function and Participation Scales (M-FUN) and assess the validity of U.S. norms for Israeli children. METHOD. All components of the M-FUN were translated, and a pilot study revealed a need for further investigation. The Hebrew M-FUN's fine, gross, and visual-motor (VM) components and M-FUN participation questionnaires were administered to 267 Israeli children (128 boys, 139 girls; mean age = 59.21 mo, standard deviation = 17.84). RESULTS. Significant correlations supported construct validity between age and all motor and participation scores as well as age-group differences. Significant differences between the U.S. and Israeli samples were found only for the VM score. Participation and motor scores were significantly correlated. CONCLUSION. Although VM score results should be interpreted with caution, we provide evidence for use of the fine and gross motor norms and the U.S. criterion-referenced participation scores of the M-FUN with Israeli children. Copyright © 2014 by the American Occupational Therapy Association, Inc.

  16. Secular changes in Earth's shape and surface mass loading derived from combinations of reprocessed global GPS networks

    Science.gov (United States)

    Booker, David; Clarke, Peter J.; Lavallée, David A.

    2014-09-01

    The changing distribution of surface mass (oceans, atmospheric pressure, continental water storage, groundwater, lakes, snow and ice) causes detectable changes in the shape of the solid Earth, on time scales ranging from hours to millennia. Transient changes in the Earth's shape can, regardless of cause, be readily separated from steady secular variation in surface mass loading, but other secular changes due to plate tectonics and glacial isostatic adjustment (GIA) cannot. We estimate secular station velocities from almost 11 years of high quality combined GPS position solutions (GPS weeks 1,000-1,570) submitted as part of the first international global navigation satellite system service reprocessing campaign. Individual station velocities are estimated as a linear fit, paying careful attention to outliers and offsets. We remove a suite of a priori GIA models, each with an associated set of plate tectonic Euler vectors estimated by us; the latter are shown to be insensitive to the a priori GIA model. From the coordinate time series residuals after removing the GIA models and corresponding plate tectonic velocities, we use mass-conserving continental basis functions to estimate surface mass loading including the secular term. The different GIA models lead to significant differences in the estimates of loading in selected regions. Although our loading estimates are broadly comparable with independent estimates from other satellite missions, their range highlights the need for better, more robust GIA models that incorporate 3D Earth structure and accurately represent 3D surface displacements.

  17. The unknown-unknowns: Revealing the hidden insights in massive biomedical data using combined artificial intelligence and knowledge networks

    Directory of Open Access Journals (Sweden)

    Chris Yoo

    2017-12-01

    Full Text Available Genomic data is estimated to be doubling every seven months with over 2 trillion bases from whole genome sequence studies deposited in Genbank in just the last 15 years alone. Recent advances in compute and storage have enabled the use of artificial intelligence techniques in areas such as feature recognition in digital pathology and chemical synthesis for drug development. To apply A.I. productively to multidimensional data such as cellular processes and their dysregulation, the data must be transformed into a structured format, using prior knowledge to create contextual relationships and hierarchies upon which computational analysis can be performed. Here we present the organization of complex data into hypergraphs that facilitate the application of A.I. We provide an example use case of a hypergraph containing hundreds of biological data values and the results of several classes of A.I. algorithms applied in a popular compute cloud. While multiple, biologically insightful correlations between disease states, behavior, and molecular features were identified, the insights of scientific import were revealed only when exploration of the data included visualization of subgraphs of represented knowledge. The results suggest that while machine learning can identify known correlations and suggest testable ones, the greater probability of discovering unexpected relationships between seemingly independent variables (unknown-unknowns requires a context-aware system – hypergraphs that impart biological meaning in nodes and edges. We discuss the implications of a combined hypergraph-A.I. analysis approach to multidimensional data and the pre-processing requirements for such a system.

  18. 'You're in FunDzaland': Pre-service teachers (reimagine audience on a creative writing course

    Directory of Open Access Journals (Sweden)

    Belinda Mendelowitz

    2016-07-01

    Full Text Available This study explores how collaborative writing for a digital platform can enable students to (re imagine audience. Although in the context of process writing peer feedback is foreground, in practice, its effectiveness is uneven. The digital revolution offers new opportunities for alternative peer feedback through collaborative writing and re-imagining self and other in the process. This study examines data from a creative writing course in which pre-service teachers wrote collaborative short stories for the FunDza digital site and individual reflective essays about the process. The study’s research questions are the following: (1 what were the affordances of this multilayered audience for engaging the students’ imaginations? (2 How did this process of (reimagining audience impact on students’ conceptions of themselves as writers? The data set comprised 16 collaboratively authored stories (published on the site and 34 individual reflective essays. Six of the latter were selected for detailed analysis. Hence, the data for this study encompass detailed analysis of two groups’ reflective essays on the process of writing their stories. These groups were selected because they exemplified contrasting collaborative, imaginative writing processes. Group 1 was familiar with the FunDza audience and context, while Group 2 struggled to imagine it. Thematic content analysis was used for analysis. Each essay was read first in relation to the entire data set, then in relation to the other reflections in the author’s group. The combination of gearing stories towards the FunDza audience and writing stories collaboratively created two sets of audiences that writers needed to hold in mind simultaneously. Analysis indicates that both audiences challenged students to make imaginative leaps into the minds of an unfamiliar audience, deepening their understanding of the writing process. It also highlights students’ mastery of writing discourses and increasing

  19. Combining Temporal and Spectral Information with Spatial Mapping to Identify Differences between Phonological and Semantic Networks: A Magnetoencephalographic Approach.

    Science.gov (United States)

    McNab, Fiona; Hillebrand, Arjan; Swithenby, Stephen J; Rippon, Gina

    2012-01-01

    Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14-30 Hz) and gamma (30-50 Hz) frequency bands were analyzed in pre-selected time windows of 350-550 and 500-700 ms In left temporal regions, both tasks elicited power changes in the same time window (350-550 ms), but with different spectral characteristics, low beta (14-20 Hz) for the phonological task and high beta (20-30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30-50 Hz), but in different time windows, 500-700 ms for the phonological task and 350-550 ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20-30 Hz beta frequency band but in different time windows, 350-550 ms for the phonological task and 500-700 ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and frequency domains.

  20. Combination of support vector machine, artificial neural network and random forest for improving the classification of convective and stratiform rain using spectral features of SEVIRI data

    Science.gov (United States)

    Lazri, Mourad; Ameur, Soltane

    2018-05-01

    A model combining three classifiers, namely Support vector machine, Artificial neural network and Random forest (SAR) is designed for improving the classification of convective and stratiform rain. This model (SAR model) has been trained and then tested on a datasets derived from MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager). Well-classified, mid-classified and misclassified pixels are determined from the combination of three classifiers. Mid-classified and misclassified pixels that are considered unreliable pixels are reclassified by using a novel training of the developed scheme. In this novel training, only the input data corresponding to the pixels in question to are used. This whole process is repeated a second time and applied to mid-classified and misclassified pixels separately. Learning and validation of the developed scheme are realized against co-located data observed by ground radar. The developed scheme outperformed different classifiers used separately and reached 97.40% of overall accuracy of classification.

  1. Comparison of the efficacy among multiple chemotherapeutic interventions combined with radiation therapy for patients with cervix cancer after surgery: A network meta-analysis.

    Science.gov (United States)

    Chang, Lei; Guo, Ruixia

    2017-07-25

    Cervix cancer was the second most common cancer in female. However, there was no network meta-analysis (NMA) comparing the efficacy of the multiple chemotherapeutic interventions combined with radiation therapy in patients after operation. Randomized controlled trials were retrieved from PubMed, Embase and Cochrane Library. Overall survival (OS), recurrence-free survival (RFS), incidence of recurrence and distant metastasis were the main outcomes, particularly 5-year OS and PFS were considered as primary outcomes. Furthermore, the hazard ratio (HR) or odds ratio (OR) and their 95% credible intervals (CrIs) were extracted. The surface under cumulative ranking curve (SUCRA) was also used in this NMA. A total of 39 eligible trials with 8,952 patients were included and 22 common chemotherapies were evaluated in this meta-analysis. For OS, cisplatin+fluorouracil+hydroxyurea, fluorouracil+mitomycin C, cisplatin and cisplatin+fluorouracil were better than placebo. As for RFS, cisplatin+fluorouracil, fluorouracil+mitomycin C, and cisplatin alone had the significant superiority compared with placebo. In terms of incidence of recurrence, the optimal drug combination was cisplatin+ifosfamide (0.93) based on SUCRA. Moreover, epirubicin (OR = 0.28, 95% CrI: 0.08-0.91) was the only one had the distinguished potency in reducing the occurrence of distant metastasis with a SUCRA rank probability of 0.88. We recommended cisplatin+fluorouracil+hydroxyurea and cisplatin+docetaxel for their good efficacy in long term survival. Meanwhile, the combination of multiple drugs with different mechanisms worked better.

  2. A combined neural network and mechanistic approach for the prediction of corrosion rate and yield strength of magnesium-rare earth alloys

    International Nuclear Information System (INIS)

    Birbilis, N.; Cavanaugh, M.K.; Sudholz, A.D.; Zhu, S.M.; Easton, M.A.; Gibson, M.A.

    2011-01-01

    Research highlights: → This study presents a body of corrosion data for a set of custom alloys and displays this in multivariable space. These alloys represent the next generation of Mg alloys for auto applications. → The data is processed using an ANN model, which makes it possible to yield a single expression for prediction of corrosion rate (and strength) as a function of any input composition (of Ce, La or Nd between 0 and 6 wt.%). → The relative influence of the various RE elements on corrosion is assessed, with the outcome that Nd additions can offer comparable strength with minimal rise in corrosion rate. → The morphology and solute present in the eutectic region itself (as opposed to just the intermetallic presence) was shown - for the first time - to also be a key contributor to corrosion. → The above approach sets the foundation for rational alloy design of alloys with corrosion performance in mind. - Abstract: Additions of Ce, La and Nd to Mg were made in binary, ternary and quaternary combinations up to ∼6 wt.%. This provided a dataset that was used in developing a neural network model for predicting corrosion rate and yield strength. Whilst yield strength increased with RE additions, corrosion rates also systematically increased, however, this depended on the type of RE element added and the combination of elements added (along with differences in intermetallic morphology). This work is permits an understanding of Mg-RE alloy performance, and can be exploited in Mg alloy design for predictable combinations of strength and corrosion resistance.

  3. Kids just wanna have fun: Children's experiences of a weight management programme.

    Science.gov (United States)

    Watson, Libby A; Baker, Martyn C; Chadwick, Paul M

    2016-05-01

    To explore children's accounts of their experiences of the UK's largest childhood obesity programme, MEND (Mind, Exercise, Nutrition...Do it!) (See www.mendprogramme.org). Semi-structured interviews were conducted with children who had completed the MEND obesity programme. Interviews were transcribed verbatim and analysed using Interpretative Phenomenological Analysis (IPA). Fourteen children spanning diverse areas of London comprised this study (eight male, six female), aged between 11 and 14 years and in secondary school. Participants were interviewed a year after completing one of the London-based MEND obesity programmes. This article focuses on the most common and striking theme to emerge from the original dataset (The complete analysis may be found in L. Watson, Unpublished doctoral thesis): Fun. Subthemes were: 'going with the flow'; active participation in activities that led to new experiences ('actually doing it' - seeing the fun side); the importance of others in the experience of fun ('you do games in unity' - 'it's not as fun on your own'). Children have fun when engaged in interactive and varied activities with opportunity for individual feedback and improvement. When designing childhood obesity programmes, conditions that optimise children's experience of fun should be emphasised over didactic and risk-heavy information pertaining to childhood obesity. What is already known on this subject? Continued growth in childhood obesity and its associated health problems, psychological effects, and economic burden make tackling childhood obesity a public health priority. Multicomponent lifestyle interventions to treat childhood obesity within the community have been shown to reduce overweight and obesity from pre- to post-treatment, increase self-esteem, and are found to be acceptable by parents. MEND is the most widely disseminated evidence-based programme of this kind in the United Kingdom. What does this study add? This study is the first qualitative study

  4. Fun and games in Berkeley: the early years (1956-2013).

    Science.gov (United States)

    Tinoco, Ignacio

    2014-01-01

    Life at Berkeley for the past 57 years involved research on the thermodynamics, kinetics, and spectroscopic properties of RNA to better understand its structures, interactions, and functions. We (myself and all the graduate students and postdocs who shared in the fun) began with dinucleoside phosphates and slowly worked our way up to megadalton-sized RNA molecular motors. We used UV absorption, circular dichroism, circular intensity differential scattering, fluorescence, NMR, and single-molecule methods. We learned a lot and had fun doing it.

  5. Enjoyable learning: the role of humour, games, and fun activities in nursing and midwifery education.

    Science.gov (United States)

    Baid, Heather; Lambert, Nicky

    2010-08-01

    Education that captures the attention of students is an essential aspect of promoting meaningful, active learning. Rather than standing at the front of a group of learners simply speaking about a topic, teachers have the opportunity of livening up their teaching with humour, games, and other fun activities. This article critically evaluates the benefits and limitations of humour within nursing education as well as the use of games and fun activities as teaching strategies. Examples of various games and interactive activities are also provided. Copyright 2009 Elsevier Ltd. All rights reserved.

  6. Fun with Foodella: A Pilot Study for Determining the Efficacy of a 2nd Grade Nutrition and Physical Activity Curriculum

    Science.gov (United States)

    Winter, Elizabeth M.; Stluka, Suzanne; Wells, Karlys; Wey, Howard; Kemmer, Teresa M.

    2012-01-01

    Fun with Foodella is a nutrition and physical activity workbook designed for elementary-aged youth. The objective was to determine if the Fun with Foodella program increased participant preference for fruit, vegetables, low-fat dairy products, and physical activity. Four intervention (53 students) and four control (68 students) schools…

  7. Falls Risk Prediction for Older Inpatients in Acute Care Medical Wards: Is There an Interest to Combine an Early Nurse Assessment and the Artificial Neural Network Analysis?

    Science.gov (United States)

    Beauchet, O; Noublanche, F; Simon, R; Sekhon, H; Chabot, J; Levinoff, E J; Kabeshova, A; Launay, C P

    2018-01-01

    Identification of the risk of falls is important among older inpatients. This study aims to examine performance criteria (i.e.; sensitivity, specificity, positive predictive value, negative predictive value and accuracy) for fall prediction resulting from a nurse assessment and an artificial neural networks (ANNs) analysis in older inpatients hospitalized in acute care medical wards. A total of 848 older inpatients (mean age, 83.0±7.2 years; 41.8% female) admitted to acute care medical wards in Angers University hospital (France) were included in this study using an observational prospective cohort design. Within 24 hours after admission of older inpatients, nurses performed a bedside clinical assessment. Participants were separated into non-fallers and fallers (i.e.; ≥1 fall during hospitalization stay). The analysis was conducted using three feed forward ANNs (multilayer perceptron [MLP], averaged neural network, and neuroevolution of augmenting topologies [NEAT]). Seventy-three (8.6%) participants fell at least once during their hospital stay. ANNs showed a high specificity, regardless of which ANN was used, and the highest value reported was with MLP (99.8%). In contrast, sensitivity was lower, with values ranging between 98.4 to 14.8%. MLP had the highest accuracy (99.7). Performance criteria for fall prediction resulting from a bedside nursing assessment and an ANNs analysis was associated with a high specificity but a low sensitivity, suggesting that this combined approach should be used more as a diagnostic test than a screening test when considering older inpatients in acute care medical ward.

  8. Spectrophotometric determination of iron species using a combination of artificial neural networks and dispersive liquid–liquid microextraction based on solidification of floating organic drop

    International Nuclear Information System (INIS)

    Moghadam, Masoud Rohani; Shabani, Ali Mohammad Haji; Dadfarnia, Shayessteh

    2011-01-01

    Highlights: ► Combination of DLLME-SFO/fiber optic-linear array detection/chemometric methods. ► Simultaneous determination of complexes with overlapping spectra. ► A novel DLLME-SFO method is proposed for extraction of iron species. ► The extracted iron species are simultaneous determined using PC-ANNs. ► The enhancement factor of 162 and 125 are achieved for Fe 3+ and Fe 2+ , respectively. - Abstract: A dispersive liquid–liquid microextraction based on solidification of floating organic drop (DLLME-SFO) and artificial neural networks method was developed for the simultaneous separation/preconcentration and speciation of iron in water samples. In this method, an appropriate mixture of ethanol (as the disperser solvent) and 1-undecanol (as the extracting solvent) containing appropriate amount of 2-thenoyltrifluoroacetone (TTA) (as the complexing agent) was injected rapidly into the water sample containing iron (II) and iron (III) species. At this step, the iron species interacted with the TTA and extracted into the 1-undecanol. After the phase separation, the absorbance of the extracted irons was measured in the wavelength region of 450–600 nm. The artificial neural networks were then applied for simultaneous determination of individual iron species. Under optimum conditions, the calibration graphs were linear in the range of 95–1070 μg L −1 and 31–350 μg L −1 with detection limits of 25 and 8 μg L −1 for iron (II) and iron (III), respectively. The relative standard deviations (R.S.D., n = 6) were lower than 4.2%. The enhancement factor of 162 and 125 were obtained for Fe 3+ and Fe 2+ ions, respectively. The procedure was applied to power plant drum water and several potable water samples; and accuracy was assessed through the recovery experiments and independent analysis by graphite furnace atomic absorption spectrometry.

  9. Simulating Cyber-Attacks for Fun and Profit

    OpenAIRE

    Futoransky, Ariel; Miranda, Fernando; Orlicki, Jose; Sarraute, Carlos

    2010-01-01

    We introduce a new simulation platform called Insight, created to design and simulate cyber-attacks against large arbitrary target scenarios. Insight has surprisingly low hardware and configuration requirements, while making the simulation a realistic experience from the attacker's standpoint. The scenarios include a crowd of simulated actors: network devices, hardware devices, software applications, protocols, users, etc. A novel characteristic of this tool is to simulate vulnerabilities (in...

  10. Constraining CO2 tower measurements in an inhomogeneous area with anthropogenic emissions using a combination of car-mounted instrument campaigns, aircraft profiles, transport modeling and neural networks

    Science.gov (United States)

    Schmidt, A.; Rella, C.; Conley, S. A.; Goeckede, M.; Law, B. E.

    2013-12-01

    The NOAA CO2 observation network in Oregon has been enhanced by 3 new towers in 2012. The tallest tower in the network (270 m), located in Silverton in the Willamette Valley is affected by anthropogenic emissions from Oregon's busiest traffic routes and urban centers. In summer 2012, we conducted a measurement campaign using a car-mounted PICARRO CRDS CO2/CO analyzer. Over 3 days, the instrument was driven over 1000 miles throughout the northwestern portion of Oregon measuring the CO/ CO2 ratios on main highways, back roads in forests, agricultural sites, and Oregon's biggest urban centers. By geospatial analyses we obtained ratios of CO/ CO2 over distinct land cover types divided into 10 classes represented in the study area. Using the coupled WRF-STILT transport model we calculated the footprints of nearby CO/ CO2 observation towers for the corresponding days of mobile road measurements. Spatiotemporally assigned source areas in combination with the land use classification were then used to calculate specific ratios of CO (anthropogenic origins) and CO2 to separate the anthropogenic portion of CO2 from the mixing ratio time series measured at the tower in Silverton. The WRF modeled boundary layer heights used in out study showed some differences compared to the boundary layer heights derived from profile data of wind, temperature, and humidity measured with an airplane in August, September, and November 2012, repeatedly over 5 tower locations. A Bayesian Regularized Artificial Neural Network (BRANN) was used to correct the boundary layer height calculated with WRF with a temporal resolution of 20 minutes and a horizontal resolution of 4 km. For that purpose the BRANN was trained using height profile data from the flight campaigns and spatiotemporally corresponding meteorological data from WRF. Our analyses provide information needed to run inverse modeling of CO2 exchange in an area that is affected by sources that cannot easily be considered by biospheric models

  11. Comparative efficacy and acceptability of antidepressants, psychological interventions, and their combination for depressive disorder in children and adolescents: protocol for a network meta-analysis

    Science.gov (United States)

    Zhou, Xinyu; Cipriani, Andrea; Zhang, Yuqing; Cuijpers, Pim; Hetrick, Sarah E; Weisz, John R; Pu, Juncai; Giovane, Cinzia Del; Furukawa, Toshiaki A; Barth, Jürgen; Coghill, David; Leucht, Stefan; Yang, Lining; Ravindran, Arun V; Xie, Peng

    2017-01-01

    Introduction Depressive disorder is common in children and adolescents, with important consequences and serious impairments in terms of personal and social functioning. While both pharmacological and psychological interventions have been shown to be effective, there is still uncertainty about the balance between these and what treatment strategy should be preferred in clinical practice. Therefore, we aim to compare and rank in a network meta-analysis (NMA) the commonly used psychological, pharmacological and combined interventions for depressive disorder in children and adolescents. Methods and analysis We will update the literature search of two previous NMAs for the identification of trials of antidepressant and psychotherapy alone for depressive disorder in children and adolescents. For identification of trials of combination interventions, seven databases (PubMed, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science, PsycINFO, CINAHL, LiLACS) will be searched from date of inception. We will also search ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform and check relevant reports on the US Food and Drug Administration website for unpublished data. Building on our previous findings in the field, we will include any commonly prescribed oral antidepressants and any manualised or structured psychotherapies, as well as their combinations. Randomised controlled trials assessing any active intervention against active comparator or pill placebo/psychological controls in acute treatment for depressive disorder in children and adolescents will be included. The primary outcomes will be efficacy (mean change in depressive symptoms), and acceptability of treatment (dropout rate due to any cause). The secondary outcomes will be remission rate, tolerability of treatment (dropouts for adverse events), as well as suicide-related outcomes (suicidal behaviour or ideation). We will perform Bayesian NMAs for all relative outcome

  12. Comparative efficacy and acceptability of antidepressants, psychological interventions, and their combination for depressive disorder in children and adolescents: protocol for a network meta-analysis.

    Science.gov (United States)

    Zhou, Xinyu; Cipriani, Andrea; Zhang, Yuqing; Cuijpers, Pim; Hetrick, Sarah E; Weisz, John R; Pu, Juncai; Giovane, Cinzia Del; Furukawa, Toshiaki A; Barth, Jürgen; Coghill, David; Leucht, Stefan; Yang, Lining; Ravindran, Arun V; Xie, Peng

    2017-08-11

    Depressive disorder is common in children and adolescents, with important consequences and serious impairments in terms of personal and social functioning. While both pharmacological and psychological interventions have been shown to be effective, there is still uncertainty about the balance between these and what treatment strategy should be preferred in clinical practice. Therefore, we aim to compare and rank in a network meta-analysis (NMA) the commonly used psychological, pharmacological and combined interventions for depressive disorder in children and adolescents. We will update the literature search of two previous NMAs for the identification of trials of antidepressant and psychotherapy alone for depressive disorder in children and adolescents. For identification of trials of combination interventions, seven databases (PubMed, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science, PsycINFO, CINAHL, LiLACS) will be searched from date of inception. We will also search ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform and check relevant reports on the US Food and Drug Administration website for unpublished data. Building on our previous findings in the field, we will include any commonly prescribed oral antidepressants and any manualised or structured psychotherapies, as well as their combinations. Randomised controlled trials assessing any active intervention against active comparator or pill placebo/psychological controls in acute treatment for depressive disorder in children and adolescents will be included. The primary outcomes will be efficacy (mean change in depressive symptoms), and acceptability of treatment (dropout rate due to any cause). The secondary outcomes will be remission rate, tolerability of treatment (dropouts for adverse events), as well as suicide-related outcomes (suicidal behaviour or ideation). We will perform Bayesian NMAs for all relative outcome measures. Subgroup analyses and

  13. Disentangling fun and enjoyment in exergames using an expanded design, play, experience framework: A narrative review

    Science.gov (United States)

    With exergames (as with physical activity in general), more intense and longer-duration game play should accrue more health benefits. Exergames, however, appear to be played for relatively short durations, often at medium or lower intensities. Ostensibly games are played for fun or enjoyment. Enhanc...

  14. A socio-musical analysis of Ayo Bankole's choral music: Fun Mi N ...

    African Journals Online (AJOL)

    ... diverse African elements and major features of African music are present in the melody, rhythm and harmony of the vocal work. The paper concluded that Fun Mi N'Ibeji contained both elements of traditional Nigerian music and Western classical music which are employed in expressing the traditional beliefs of the Yoruba ...

  15. Udspring og fald i Alison Bechdels grafiske erindringsværk: "Fun Home. A Family Tragicomic"

    DEFF Research Database (Denmark)

    Gammelgaard, Lasse

    2012-01-01

    Alison Bechdel’s Fun Home. A Family Tragicomic is a graphic memoir about the author’s own coming-out story and her father’s homosexuality and (probable) suicide. It endeavors to give an accurate account of the past, but the telling is simultaneously replete with fictionalising elements. This paper...

  16. Whole Grains and Food Fun in an After-School Program

    Science.gov (United States)

    Gilboy, Mary Beth

    2009-01-01

    Programs in community-based, after-school settings are ideal to teach children about healthy eating. Objectives: After completing this Whole Grains & Food Fun lesson, children will be able to: (1) list at least two benefits of eating more whole grains, (2) demonstrate skills involved in child-friendly, basic food preparation, and (3) choose a…

  17. Food & Fun op de boerderij : Consumenten komen graag op de boerderij

    NARCIS (Netherlands)

    Stil, L.; PPO Akkerbouw, Groene Ruimte en Vollegrondsgroente

    2009-01-01

    Een Food- & Fun-boerderij geeft consumenten een goed gevoel en daarom komen ze er graag. Ze komen om te genieten van het buiten zijn en omdat ze er wat kunnen leren. De ervaring van het boerenleven zorgt voor een stapje uit de dagelijkse werkelijkheid met rust, ruimte, ritme en natuur van de

  18. Emerald Dragon Bites vs Veggie Beans: Fun Food Names Increase Children's Consumption of Novel Healthy Foods

    Science.gov (United States)

    Musher-Eizenman, Dara R.; Oehlhof, Marissa Wagner; Young, Kathleen M.; Hauser, Jessica C.; Galliger, Courtney; Sommer, Alyssa

    2011-01-01

    Caregivers often struggle with food neophobia on the part of young children. This study examined whether labeling novel healthy foods with fun names would increase children's willingness to try those foods and encourage them to eat more of those foods in a child care setting. Thirty-nine toddler and preschool age children (mean age = 3.9 years)…

  19. Função Poética e Televisão

    Directory of Open Access Journals (Sweden)

    Anna Maria Balogh

    1990-10-01

    Full Text Available Ao empreendermos uma rápida usca nos guardados da memória, verificamos a existência de conceitos arraigados no tocante ao que se considera artístico". Alguns dos conceitos de "artisticidade" revelam vinculações estreitas com as funções "estética" e "poética".

  20. Sandy Point Fun Run: A Context for Understanding and Using Scale

    Science.gov (United States)

    Roche, Anne

    2013-01-01

    In the middle years of school, it is important that mathematics is challenging, engaging and focuses on worthwhile mathematics. In this article, Anne Roche describes a lesson that seemed to have all three of these characteristics, as students grappled with issues of scale to create a fun run, given a range of challenging mathematical constraints.…

  1. Improving Emotion Regulation and Sibling Relationship Quality: The More Fun with Sisters and Brothers Program

    Science.gov (United States)

    Kennedy, Denise E.; Kramer, Laurie

    2008-01-01

    We examined the role of emotion regulation (ER) in improving sibling relationship quality (SRQ) by evaluating the More Fun With Sisters and Brothers Program where 4- to 8-year-old siblings from 95 families were taught emotional and social competencies. Parents reported on SRQ and ER, and sibling interactions were observed in homes. SRQ and ER…

  2. Generational Attitudes toward Workplace Fun and Their Relationship to Job Satisfaction

    Science.gov (United States)

    Attebery, Esther

    2017-01-01

    Purpose: The purpose of this quantitative study was to examine attitudes toward workplace fun and overall job satisfaction of baby boomer, Generation X, and millennial staff employees at a Christian university in California, and determine if there is a predictive relationship between them. Conceptual Framework: The framework was developed from…

  3. Calcium-aluminum-rich inclusions with fractionation and unknown nuclear effects (FUN CAIs)

    DEFF Research Database (Denmark)

    Krot, Alexander N.; Nagashima, Kazuhide; Wasserburg, Gerald J.

    2014-01-01

    We present a detailed characterization of the mineralogy, petrology, and oxygen isotopic compositions of twelve FUN CAIs, including C1 and EK1-4-1 from Allende (CV), that were previously shown to have large isotopic fractionation patterns for magnesium and oxygen, and large isotopic anomalies...

  4. Developing a coding scheme for detecting usability and fun problems in computer games for young children

    NARCIS (Netherlands)

    Barendregt, W.; Bekker, M.M.

    2006-01-01

    This article describes the development and assessment of a coding scheme for finding both usability and fun problems through observations of young children playing computer games during user tests. The proposed coding scheme is based on an existing list of breakdown indication types of the detailed

  5. Where in the World Is Ronald McDonald? Involving Families in Geographic Fun!

    Science.gov (United States)

    Mater, Marty

    2017-01-01

    A Family Geography Night (FGN) kit can be used to bring families together, teach about the world, give parents the opportunity to share their beliefs, and participate in the educational system while having fun! Geography is an essential element of twenty-first-century education. More than just maps, geography is the interaction of cultures,…

  6. Sun Protection is Fun! A Skin Cancer Prevention Program for Preschools.

    Science.gov (United States)

    Tripp, Mary K.; Herrmann, Nancy B.; Parcel, Guy S.; Chamberlin, Robert M.; Gritz, Ellen R.

    2000-01-01

    Describes the Sun Protection is Fun! skin cancer prevention program for preschool children that features intervention methods grounded in social cognitive theory and emphasizes symbolic modeling, vicarious learning, enactive mastery experiences, and persuasion. Program components include a curriculum and teacher's guide, videos, newsletters,…

  7. A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

    Science.gov (United States)

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

  8. Seamless Combination of Fluorescence-Activated Cell Sorting and Hanging-Drop Networks for Individual Handling and Culturing of Stem Cells and Microtissue Spheroids.

    Science.gov (United States)

    Birchler, Axel; Berger, Mischa; Jäggin, Verena; Lopes, Telma; Etzrodt, Martin; Misun, Patrick Mark; Pena-Francesch, Maria; Schroeder, Timm; Hierlemann, Andreas; Frey, Olivier

    2016-01-19

    Open microfluidic cell culturing devices offer new possibilities to simplify loading, culturing, and harvesting of individual cells or microtissues due to the fact that liquids and cells/microtissues are directly accessible. We present a complete workflow for microfluidic handling and culturing of individual cells and microtissue spheroids, which is based on the hanging-drop network concept: The open microfluidic devices are seamlessly combined with fluorescence-activated cell sorting (FACS), so that individual cells, including stem cells, can be directly sorted into specified culturing compartments in a fully automated way and at high accuracy. Moreover, already assembled microtissue spheroids can be loaded into the microfluidic structures by using a conventional pipet. Cell and microtissue culturing is then performed in hanging drops under controlled perfusion. On-chip drop size control measures were applied to stabilize the system. Cells and microtissue spheroids can be retrieved from the chip by using a parallelized transfer method. The presented methodology holds great promise for combinatorial screening of stem-cell and multicellular-spheroid cultures.

  9. Towards modeling of combined cooling, heating and power system with artificial neural network for exergy destruction and exergy efficiency prognostication of tri-generation components

    International Nuclear Information System (INIS)

    Taghavifar, Hadi; Anvari, Simin; Saray, Rahim Khoshbakhti; Khalilarya, Shahram; Jafarmadar, Samad; Taghavifar, Hamid

    2015-01-01

    The current study is an attempt to address the investigation of the CCHP (combined cooling, heating and power) system when 10 input variables were chosen to analyze 10 most important objective output parameters. Moreover, ANN (artificial neural network) was successfully applied on the tri-generation system on account of its capability to predict responses with great confidence. The results of sensitivity analysis were considered as foundation for selecting the most suitable and potent input parameters of the supposed cycle. Furthermore, the best ANN topology was attained based on the least amount of MSE and number of iterations. Consequently, the trainlm (Levenberg–Marquardt) training approach with 10-9-10 configuration has been exploited for ANN modeling in order to give the best output correspondence. The maximum MRE = 1.75% (mean relative error) and minimum R 2  = 0.984 represents the reliability and outperformance of the developed ANN over common conventional thermodynamic analysis carried out by EES (engineering equation solver) software. - Highlights: • Exergy analysis is undertaken for CCHP components based on operative factors. • ANN tool is applied to obtained database from thermodynamic analyses session. • The best ANN topology is detected at 10-9-10 with trainlm learning algorithm. • The input and output layer parameters were selected based on sensitivity analysis.

  10. The Combination of Trichoderma harzianum and Chemical Fertilization Leads to the Deregulation of Phytohormone Networking, Preventing the Adaptive Responses of Tomato Plants to Salt Stress.

    Science.gov (United States)

    Rubio, M B; Hermosa, Rosa; Vicente, Rubén; Gómez-Acosta, Fabio A; Morcuende, Rosa; Monte, Enrique; Bettiol, Wagner

    2017-01-01

    Plants have evolved effective mechanisms to avoid or reduce the potential damage caused by abiotic stresses. In addition to biocontrol abilities, Trichoderma genus fungi promote growth and alleviate the adverse effects caused by saline stress in plants. Morphological, physiological, and molecular changes were analyzed in salt-stressed tomato plants grown under greenhouse conditions in order to investigate the effects of chemical and biological fertilizations. The application of Trichoderma harzianum T34 to tomato seeds had very positive effects on plant growth, independently of chemical fertilization. The application of salt stress significantly changed the parameters related to growth and gas-exchange rates in tomato plants subject to chemical fertilization. However, the gas-exchange parameters were not affected in unfertilized plants under the same moderate saline stress. The combined application of T34 and salt significantly reduced the fresh and dry weights of NPK-fertilized plants, while the opposite effects were detected when no chemical fertilization was applied. Decaying symptoms were observed in salt-stressed and chemically fertilized plants previously treated with T34. This damaged phenotype was linked to significantly higher intercellular CO 2 and slight increases in stomatal conductance and transpiration, and to the deregulation of phytohormone networking in terms of significantly lower expression levels of the salt overlay sensitivity 1 ( SOS1 ) gene, and the genes involved in signaling abscisic acid-, ethylene-, and salicylic acid-dependent pathways and ROS production, in comparison with those observed in salt-challenged NPK-fertilized plants.

  11. A Comparison of Spectral Angle Mapper and Artificial Neural Network Classifiers Combined with Landsat TM Imagery Analysis for Obtaining Burnt Area Mapping

    Directory of Open Access Journals (Sweden)

    Marko Scholze

    2010-03-01

    Full Text Available Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN and Spectral Angle Mapper (SAM classifiers with Landsat TM satellite imagery was evaluated in a Mediterranean setting. As a case study one of the most catastrophic forest fires, which occurred near the capital of Greece during the summer of 2007, was used. The accuracy of the two algorithms in delineating the burnt area from the Landsat TM imagery, acquired shortly after the fire suppression, was determined by the classification accuracy results of the produced thematic maps. In addition, the derived burnt area estimates from the two classifiers were compared with independent estimates available for the study region, obtained from the analysis of higher spatial resolution satellite data. In terms of the overall classification accuracy, ANN outperformed (overall accuracy 90.29%, Kappa coefficient 0.878 the SAM classifier (overall accuracy 83.82%, Kappa coefficient 0.795. Total burnt area estimates from the two classifiers were found also to be in close agreement with the other available estimates for the study region, with a mean absolute percentage difference of ~1% for ANN and ~6.5% for SAM. The study demonstrates the potential of the examined here algorithms in detecting burnt areas in a typical Mediterranean setting.

  12. Inequalities and Duality in Gene Coexpression Networks of HIV-1 Infection Revealed by the Combination of the Double-Connectivity Approach and the Gini's Method

    Directory of Open Access Journals (Sweden)

    Chuang Ma

    2011-01-01

    Full Text Available The symbiosis (Sym and pathogenesis (Pat is a duality problem of microbial infection, including HIV/AIDS. Statistical analysis of inequalities and duality in gene coexpression networks (GCNs of HIV-1 infection may gain novel insights into AIDS. In this study, we focused on analysis of GCNs of uninfected subjects and HIV-1-infected patients at three different stages of viral infection based on data deposited in the GEO database of NCBI. The inequalities and duality in these GCNs were analyzed by the combination of the double-connectivity (DC approach and the Gini's method. DC analysis reveals that there are significant differences between positive and negative connectivity in HIV-1 stage-specific GCNs. The inequality measures of negative connectivity and edge weight are changed more significantly than those of positive connectivity and edge weight in GCNs from the HIV-1 uninfected to the AIDS stages. With the permutation test method, we identified a set of genes with significant changes in the inequality and duality measure of edge weight. Functional analysis shows that these genes are highly enriched for the immune system, which plays an essential role in the Sym-Pat duality (SPD of microbial infections. Understanding of the SPD problems of HIV-1 infection may provide novel intervention strategies for AIDS.

  13. Observing System Simulation Experiments for Fun and Profit

    Science.gov (United States)

    Prive, Nikki C.

    2015-01-01

    Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

  14. Improved diagnostic accuracy of Alzheimer's disease by combining regional cortical thickness and default mode network functional connectivity: Validated in the Alzheimer's disease neuroimaging initiative set

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ji Eun; Park, Bum Woo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Jung; Oh, Joo Young; Shim, Woo Hyun [Dept. of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of); Lee, Jae Hong; Roh, Jee Hoon [University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)

    2017-11-15

    To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

  15. Thermal and chemical evolution in the early solar system as recorded by FUN CAIs: Part I - Petrology, mineral chemistry, and isotopic composition of Allende FUN CAI CMS-1

    Science.gov (United States)

    Williams, C. D.; Ushikubo, T.; Bullock, E. S.; Janney, P. E.; Hines, R. R.; Kita, N. T.; Hervig, R. L.; MacPherson, G. J.; Mendybaev, R. A.; Richter, F. M.; Wadhwa, M.

    2017-03-01

    Detailed petrologic, geochemical and isotopic analyses of a new FUN CAI from the Allende CV3 meteorite (designated CMS-1) indicate that it formed by extensive melting and evaporation of primitive precursor material(s). The precursor material(s) condensed in a 16O-rich region (δ17O and δ18O ∼ -49‰) of the inner solar nebula dominated by gas of solar composition at total pressures of ∼10-3-10-6 bar. Subsequent melting of the precursor material(s) was accompanied by evaporative loss of magnesium, silicon and oxygen resulting in large mass-dependent isotope fractionations in these elements (δ25Mg = 30.71-39.26‰, δ29Si = 14.98-16.65‰, and δ18O = -41.57 to -15.50‰). This evaporative loss resulted in a bulk composition similar to that of compact Type A and Type B CAIs, but very distinct from the composition of the original precursor condensate(s). Kinetic fractionation factors and the measured mass-dependent fractionation of silicon and magnesium in CMS-1 suggest that ∼80% of the silicon and ∼85% of the magnesium were lost from its precursor material(s) through evaporative processes. These results suggest that the precursor material(s) of normal and FUN CAIs condensed in similar environments, but subsequently evolved under vastly different conditions such as total gas pressure. The chemical and isotopic differences between normal and FUN CAIs could be explained by sorting of early solar system materials into distinct physical and chemical regimes, in conjunction with discrete heating events, within the protoplanetary disk.

  16. Fuel for Fun: a cluster-randomized controlled study of cooking skills, eating behaviors, and physical activity of 4th graders and their families

    Directory of Open Access Journals (Sweden)

    Leslie Cunningham-Sabo

    2016-05-01

    parents over the length of the project. Discussion The Fuel for Fun study design allows for impact assessment of school-, family- and online parent-based intervention components separately and in combination. Study strengths include use of theory- and evidence-based programs, valid child and parent self-report instruments, and objective measures of food, cooking, and physical activity behaviors at the individual, family and school levels. Parent involvement and engagement is examined through multiple strategies. Trial registration Clinicaltrials.gov registration number NCT02491294 . Registered 7 July, 2015.

  17. Fuel for Fun: a cluster-randomized controlled study of cooking skills, eating behaviors, and physical activity of 4th graders and their families.

    Science.gov (United States)

    Cunningham-Sabo, Leslie; Lohse, Barbara; Smith, Stephanie; Browning, Ray; Strutz, Erin; Nigg, Claudio; Balgopal, Meena; Kelly, Kathleen; Ruder, Elizabeth

    2016-05-26

    for Fun study design allows for impact assessment of school-, family- and online parent-based intervention components separately and in combination. Study strengths include use of theory- and evidence-based programs, valid child and parent self-report instruments, and objective measures of food, cooking, and physical activity behaviors at the individual, family and school levels. Parent involvement and engagement is examined through multiple strategies. Clinicaltrials.gov registration number NCT02491294 . Registered 7 July, 2015.

  18. Oh What FUN We've Had! Reflections on the Past and a Look to the Future.

    Science.gov (United States)

    Dickinson, Shelly D

    2012-01-01

    In 2011 FUN celebrated 20 years of training tomorrow's neuroscientists today. Over the past two decades we've become an international organization of members dedicated to excellence in teaching and research at the undergraduate level. FUN has enacted its mission through our flagship journal JUNE, student travel awards, faculty awards, education workshops, and regional conferences. More recent initiatives include the equipment loan program, department/program consulting service, the honor society Nu Rho Psi, and neuroscience study abroad opportunities. FUN is poised to continue enhancing undergraduate neuroscience education and research over the next 20 years.

  19. A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

    Directory of Open Access Journals (Sweden)

    Han Kyungsook

    2010-06-01

    Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for

  20. Roles of the combined irrigation, drainage, and storage of the canal network in improving water reuse in the irrigation districts along the lower Yellow River, China

    Science.gov (United States)

    Liu, Lei; Luo, Yi; He, Chansheng; Lai, Jianbin; Li, Xiubin

    2010-09-01

    SummaryThe commonly used irrigation system in the irrigation districts (with a combined irrigation area of 3.334 × 10 6 ha) along the lower Yellow River of China is canal network. It delivers water from the Yellow River to the fields, collects surface runoff and drainage from cropland, and stores both of them for subsequent irrigation uses. This paper developed a new combined irrigation, drainage, and storage (CIDS) module for the SWAT2000 model, simulated the multiple roles of the CIDS canal system, and estimated its performance in improving water reuse in the irrigation districts under different irrigation and water diversion scenarios. The simulation results show that the annual evapotranspiration (ET) of the double-cropping winter wheat and summer maize was the highest under the full irrigation scenario (automatic irrigation), and the lowest under the no irrigation scenario. It varied between these two values when different irrigation schedules were adopted. Precipitation could only meet the water requirement of the double-cropping system by 62-96% on an annual basis; that of the winter wheat by 32-36%, summer maize by 92-123%, and cotton by 87-98% on a seasonal basis. Hence, effective irrigation management for winter wheat is critical to ensure high wheat yield in the study area. Runoff generation was closely related to precipitation and influenced by irrigation. The highest and lowest annual runoff accounted for 19% and 11% of the annual precipitation under the full irrigation and no irrigation scenarios, respectively. Nearly 70% of the annual runoff occurred during months of July and August due to the concentrated precipitation in these 2 months. The CIDS canals play an important role in delivering the diversion water from the Yellow River, intercepting the surface runoff and drainage from cropland (inflow of the CIDS canal) and recharging the shallow aquifer for later use. Roughly 14-26% of the simulated total flow in the CIDS canal system recharged

  1. Abiraterone acetate/androgen deprivation therapy combination versus docetaxel/androgen deprivation therapy combination in advanced hormone-sensitive prostate cancer: a network meta-analysis on safety and efficacy.

    Science.gov (United States)

    Kassem, Loay; Shohdy, Kyrillus S; Abdel-Rahman, Omar

    2018-05-01

    A major, yet precisely studied, shift has occurred in the treatment of advanced hormone-sensitive prostate cancer (HSPC) by the addition of docetaxel to androgen deprivation therapy (ADT) in the first line. Recently, two landmark trials showed that abiraterone acetate (AA) can be an effective alternative along with ADT in the same setting. We implemented a network meta-analysis to compare the safety and efficacy of the two combinations. PubMed database, ASCO and ESMO meeting library databases of all results published until June 2017 were searched using the keywords: "prostate cancer" AND "docetaxel" OR "abiraterone acetate". Efficacy endpoints including progression-free survival (PFS) and overall survival (OS), and safety endpoints (including treatment related deaths and selected adverse events) were assessed. Twenty relevant studies were retrieved and assessed for eligibility. Of those trials, eight were found potentially eligible. Inconsistent reporting of efficacy outcomes limited our analysis to M1 HSPC. The pooled hazard ratios (HRs) of OS and PFS of the direct comparison of abiraterone acetate plus ADT versus ADT were 0.63 (95% CI: 0.545-0.717) and 0.38 (95% CI: 0.34-0.43), respectively. Meanwhile, in the trials of docetaxel plus ADT the pooled HRs of OS and PFS were 0.75 (95% CI: 0.65-0.86) and 0.634 (95% CI: 0.57-0.70), respectively. The indirect comparison showed that the HRs of OS and PFS in DOC + ADT in comparison to AA + ADT were 1.2 (95% CI: 0.98-1.46) and 1.65 (1.40-1.94), respectively. The pooled RR of treatment-related mortality in docetaxel + ADT versus AA + ADT was 1.438 (95% CI: 0.508-4.075). Patients with metastatic HSPC (mHSPC) who received abiraterone acetate with ADT had better PFS and less toxicity compared to those receiving docetaxel with ADT. A trend towards superior OS and fewer treatment-related deaths was also observed, but was statistically non-significant. In view of lacking clear OS advantage, the choice between

  2. Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

    Science.gov (United States)

    Bertleff, Marco; Domsch, Sebastian; Weingärtner, Sebastian; Zapp, Jascha; O'Brien, Kieran; Barth, Markus; Schad, Lothar R

    2017-12-01

    Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least-squares regression (LSR) and state-of-the-art multi-step fitting (LSR-MS) in Monte-Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR-MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo-diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR-MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR-MS, 19%; LSR, 8%), D* (ANN, 21%; LSR-MS, 25%; LSR, 23%) and K (ANN, 0%; LSR-MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR-MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state-of-the-art method LSR-MS with several advantages in the estimation of IVIM-kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times. Copyright © 2017 John Wiley & Sons, Ltd.

  3. A process for assessing the feasibility of a network meta-analysis: a case study of everolimus in combination with hormonal therapy versus chemotherapy for advanced breast cancer.

    Science.gov (United States)

    Cope, Shannon; Zhang, Jie; Saletan, Stephen; Smiechowski, Brielan; Jansen, Jeroen P; Schmid, Peter

    2014-06-05

    The aim of this study is to outline a general process for assessing the feasibility of performing a valid network meta-analysis (NMA) of randomized controlled trials (RCTs) to synthesize direct and indirect evidence for alternative treatments for a specific disease population. Several steps to assess the feasibility of an NMA are proposed based on existing recommendations. Next, a case study is used to illustrate this NMA feasibility assessment process in order to compare everolimus in combination with hormonal therapy to alternative chemotherapies in terms of progression-free survival for women with advanced breast cancer. A general process for assessing the feasibility of an NMA is outlined that incorporates explicit steps to visualize the heterogeneity in terms of treatment and outcome characteristics (Part A) as well as the study and patient characteristics (Part B). Additionally, steps are performed to illustrate differences within and across different types of direct comparisons in terms of baseline risk (Part C) and observed treatment effects (Part D) since there is a risk that the treatment effect modifiers identified may not explain the observed heterogeneity or inconsistency in the results due to unexpected, unreported or unmeasured differences. Depending on the data available, alternative approaches are suggested: list assumptions, perform a meta-regression analysis, subgroup analysis, sensitivity analyses, or summarize why an NMA is not feasible. The process outlined to assess the feasibility of an NMA provides a stepwise framework that will help to ensure that the underlying assumptions are systematically explored and that the risks (and benefits) of pooling and indirectly comparing treatment effects from RCTs for a particular research question are transparent.

  4. Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA and Generalized Regression Neural Network (GRNN in Forecasting Hepatitis Incidence in Heng County, China.

    Directory of Open Access Journals (Sweden)

    Wudi Wei

    Full Text Available Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease.The autoregressive integrated moving average (ARIMA model and the generalized regression neural network (GRNN model were used to fit the incidence data from the Heng County CDC (Center for Disease Control and Prevention from January 2005 to December 2012. Then, the ARIMA-GRNN hybrid model was developed. The incidence data from January 2013 to December 2013 were used to validate the models. Several parameters, including mean absolute error (MAE, root mean square error (RMSE, mean absolute percentage error (MAPE and mean square error (MSE, were used to compare the performance among the three models.The morbidity of hepatitis from Jan 2005 to Dec 2012 has seasonal variation and slightly rising trend. The ARIMA(0,1,2(1,1,112 model was the most appropriate one with the residual test showing a white noise sequence. The smoothing factor of the basic GRNN model and the combined model was 1.8 and 0.07, respectively. The four parameters of the hybrid model were lower than those of the two single models in the validation. The parameters values of the GRNN model were the lowest in the fitting of the three models.The hybrid ARIMA-GRNN model showed better hepatitis incidence forecasting in Heng County than the single ARIMA model and the basic GRNN model. It is a potential decision-supportive tool for controlling hepatitis in Heng County.

  5. Reduced integration and differentiation of the imitation network in autism: A combined functional connectivity magnetic resonance imaging and diffusion-weighted imaging study.

    Science.gov (United States)

    Fishman, Inna; Datko, Michael; Cabrera, Yuliana; Carper, Ruth A; Müller, Ralph-Axel

    2015-12-01

    Converging evidence indicates that brain abnormalities in autism spectrum disorder (ASD) involve atypical network connectivity, but few studies have integrated functional with structural connectivity measures. This multimodal investigation examined functional and structural connectivity of the imitation network in children and adolescents with ASD, and its links with clinical symptoms. Resting state functional magnetic resonance imaging and diffusion-weighted imaging were performed in 35 participants with ASD and 35 typically developing controls, aged 8 to 17 years, matched for age, gender, intelligence quotient, and head motion. Within-network analyses revealed overall reduced functional connectivity (FC) between distributed imitation regions in the ASD group. Whole brain analyses showed that underconnectivity in ASD occurred exclusively in regions belonging to the imitation network, whereas overconnectivity was observed between imitation nodes and extraneous regions. Structurally, reduced fractional anisotropy and increased mean diffusivity were found in white matter tracts directly connecting key imitation regions with atypical FC in ASD. These differences in microstructural organization of white matter correlated with weaker FC and greater ASD symptomatology. Findings demonstrate atypical connectivity of the brain network supporting imitation in ASD, characterized by a highly specific pattern. This pattern of underconnectivity within, but overconnectivity outside the functional network is in contrast with typical development and suggests reduced network integration and differentiation in ASD. Our findings also indicate that atypical connectivity of the imitation network may contribute to ASD clinical symptoms, highlighting the role of this fundamental social cognition ability in the pathophysiology of ASD. © 2015 American Neurological Association.

  6. Characterisation of UV-cured acrylate networks by means of hydrolysis followed by aqueous size-exclusion combined with reversed-phase chromatography

    NARCIS (Netherlands)

    Peters, R.; Litvinov, V. M.; Steeman, P.; Dias, A. A.; Mengerink, Y.; van Benthem, R.; de Koster, C. G.; van der Wal, S. J.; Schoenmakers, P.

    2007-01-01

    UV-cured networks prepared from mixtures of di-functional (polyethylene-glycol di-acrylate) and mono-functional (2-ethylhexyl acrylate) acrylates were analysed after hydrolysis, by aqueous size-exclusion chromatography coupled to on-line reversed-phase liquid-chromatography. The mean network density

  7. Application of FUN3D Solver for Aeroacoustics Simulation of a Nose Landing Gear Configuration

    Science.gov (United States)

    Vatsa, Veer N.; Lockard, David P.; Khorrami, Mehdi R.

    2011-01-01

    Numerical simulations have been performed for a nose landing gear configuration corresponding to the experimental tests conducted in the Basic Aerodynamic Research Tunnel at NASA Langley Research Center. A widely used unstructured grid code, FUN3D, is examined for solving the unsteady flow field associated with this configuration. A series of successively finer unstructured grids has been generated to assess the effect of grid refinement. Solutions have been obtained on purely tetrahedral grids as well as mixed element grids using hybrid RANS/LES turbulence models. The agreement of FUN3D solutions with experimental data on the same size mesh is better on mixed element grids compared to pure tetrahedral grids, and in general improves with grid refinement.

  8. For fun and profit a history of the free and open source software revolution

    CERN Document Server

    Tozzi, Christopher

    2017-01-01

    In the 1980s, there was a revolution with far-reaching consequences -- a revolution to restore software freedom. In the early 1980s, after decades of making source code available with programs, most programmers ceased sharing code freely. A band of revolutionaries, self-described "hackers," challenged this new norm by building operating systems with source code that could be freely shared. In For Fun and Profit, Christopher Tozzi offers an account of the free and open source software (FOSS) revolution, from its origins as an obscure, marginal effort by a small group of programmers to the widespread commercial use of open source software today. Tozzi explains FOSS's historical trajectory, shaped by eccentric personalities -- including Richard Stallman and Linus Torvalds -- and driven both by ideology and pragmatism, by fun and profit. Tozzi examines hacker culture and its influence on the Unix operating system, the reaction to Unix's commercialization, and the history of early Linux development. He describes ...

  9. Kid-Friendly Veggies and Fruits: 10 Tips for Making Healthy Food Choices More Fun for Children

    Science.gov (United States)

    ... Set up a pizza-making station in the kitchen. Use whole-wheat English muffins, bagels, or pita ... veggies or fruits into a fun shape or design. 5 fruity peanut butterfly Start with carrot sticks ...

  10. The effects of chronic achievement motivation and achievement primes on the activation of achievement and fun goals.

    Science.gov (United States)

    Hart, William; Albarracín, Dolores

    2009-12-01

    This research examined the hypothesis that situational achievement cues can elicit achievement or fun goals depending on chronic differences in achievement motivation. In 4 studies, chronic differences in achievement motivation were measured, and achievement-denoting words were used to influence behavior. The effects of these variables were assessed on self-report inventories, task performance, task resumption following an interruption, and the pursuit of means relevant to achieving or having fun. Findings indicated that achievement priming (vs. control priming) activated a goal to achieve and inhibited a goal to have fun in individuals with chronically high-achievement motivation but activated a goal to have fun and inhibited a goal to achieve in individuals with chronically low-achievement motivation.

  11. "Yes! We Are Playing a Game, and It's Going to Be Fun!"

    Science.gov (United States)

    Barrett, Kelly

    2012-01-01

    Games are for playing, more often than not playing a game is a social experience, it is fun, and we all enjoy playing games. Play and playing are ways in which we learn, so how often are games part of the normal activity of the mathematics classroom? The answer, in most cases, has to be--not often. Is it that games just don't seem to fulfil the…

  12. PENGEMBANGAN MODEL PEMBELAJARAN SENAM HEALTY FUN UNTUK ANAK SLB DI KOTA MAGELANG

    Directory of Open Access Journals (Sweden)

    Bernadeta Yovina Anggitasari

    2017-02-01

    Full Text Available The purpose of research is to produce healty Gymnastics Instructional Model Development Fun, Grade V and VI in SLB-C Magelang City. This research is the development of the procedures of product development; (1 analysis, (2 develop initial product form, (3 expert validation test, (4 the first product revision, the revision of the product based on the evaluation of experts and trial I (20 students. Revised used for improvements to the initial product, (5 the trial II (30 students, (6 the revision of the final product is done based on the results of the field trials, (7 the results of a late model gymnastics healty fun for students of classes V and VI which is generated through the revision II trial. Based on the results of research trials I obtained a percentage of 87% (good, the expert evaluation is obtained percentage of 89% (good. II trial research results obtained by the percentage of 96% (excellent. From the trial I and II, there was an increase by a margin of 7%. It can be concluded that the development of gymnastics healty fun learning model can be used as an alternative to teachers provide learning materials rhythmic gymnastics penjasorkes particularly good for classes V and VI SLB-C in Magelang and gymnastic activities that teachers do on a regular basis

  13. A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

    Science.gov (United States)

    Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

    2016-02-01

    Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Smiling is fun: a Coping with Stress and Emotion Regulation Program.

    Science.gov (United States)

    Botella, Cristina; Mira, Adriana; Garcia-Palacios, Azucena; Quero, Soledad; Navarro, Ma Vicenta; Riera López Del Amo, Antonio; Molinari, Guadalupe; Castilla, Diana; Moragrega, Inés; Soler, Carla; Alcañiz, Mariano; Baños, Rosa Maria

    2012-01-01

    Emotional disorders (Anxiety disorders and Mood disorders) are one of the most common health problems worldwide, and their economic costs are very high. People suffering from emotional disorders often use maladaptive emotion regulation strategies and have low coping behaviour that contributes to the presence of clinical symptoms. For this reason, it is important to develop strategies to monitor coping and promote emotion regulation in people exposed to high levels of stress. Information and Communication Technologies (ICT) can help us in this task. Recent systematic reviews of literature on evidence-based CBT treatments delivered via the Internet show that these approaches are effective. We have developed an intervention program ICT based: Coping with Stress and Emotion Regulation Program (Smiling is Fun), a self-applied program via the Internet. Smiling is Fun follows a transdiagnostic perspective, and it is based on CBT techniques. However, it also includes other psychological strategies to improve positive mood. The aim of the present work is to describe Smiling is Fun and the study designed to test its efficacy.

  15. Sistema Computacional para Ajuste de Funções Densidade de Probabilidade

    Directory of Open Access Journals (Sweden)

    Daniel Henrique Breda Binoti

    Full Text Available RESUMO Este trabalho teve por objetivo iniciar, implementar e validar um projeto de construção de um sistema computadorizado para ajuste de funções densidade de probabilidade. O FitFD foi desenvolvido utilizando-se a linguagem de programação Java. Como ambiente de desenvolvimento foram utilizadas a IDE (Integrated Development Environment Netbeans 7.1 e a JDK 7.3 (Java Development Kit. Os testes do sistema foram realizados em ambiente Windows. Foram implementadas no sistema as seguintes funções densidade de probabilidade: Weibull (2P, 3P, 2P com dap mínimo como locação, 3P truncada, hiperbólica (2P, 3P, 2P com dap mínimo como locação, 3P truncada, log-logística (2P, 3P, 2P com dap mínimo como locação, logística generalizada, Fatigue life (2P e 3P e Frechet (2P e 3P. O sistema desenvolvido auxilia os usuários na definição e escolha da fdp que melhor atenda suas necessidades, contudo melhorias são necessárias. O projeto iniciado mostrou-se eficiente para ajustes de funções de densidade probabilidade.

  16. Green mobile networks a networking perspective

    CERN Document Server

    Ansari, Nirwan

    2016-01-01

    Combines the hot topics of energy efficiency and next generation mobile networking, examining techniques and solutions. Green communications is a very hot topic. Ever increasing mobile network bandwidth rates significantly impacts on operating costs due to aggregate network energy consumption. As such, design on 4G networks and beyond has increasingly started to focus on 'energy efficiency' or so-called 'green' networks. Many techniques and solutions have been proposed to enhance the energy efficiency of mobile networks, yet no book has provided an in-depth analysis of the energy consumption issues in mobile networks nor offers detailed theories, tools and solutions for solving the energy efficiency problems.

  17. Local Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Sørensen, Lene Tolstrup

    2011-01-01

    Online social networks have become essential for many users in their daily communication. Through a combination of the online social networks with opportunistic networks, a new concept arises: Local Social Networks. The target of local social networks is to promote social networking benefits...... in physical environment in order to leverage personal affinities in the users' surroundings. The purpose of this paper is to present and discuss the concept of local social networks as a new social communication system. Particularly, the preliminary architecture and the prototype of local social networks...

  18. Cisco Networking All-in-One For Dummies

    CERN Document Server

    Tetz, Edward

    2011-01-01

    A helpful guide on all things Cisco Do you wish that the complex topics of routers, switches, and networking could be presented in a simple, understandable presentation? With Cisco Networking All-in-One For Dummies, they are! This expansive reference is packed with all the information you need to learn to use Cisco routers and switches to develop and manage secure Cisco networks. This straightforward-by-fun guide offers expansive coverage of Cisco and breaks down intricate subjects such as networking, virtualization, and database technologies into easily digestible pieces. Drills down complex

  19. Assessment of FUN-1 vital dye staining: Yeast with a block in the vacuolar sorting pathway have impaired ability to form CIVS when stained with FUN-1 fluorescent dye.

    Science.gov (United States)

    Essary, Brandin D; Marshall, Pamela A

    2009-08-01

    FUN-1 [2-chloro-4-(2,3-dihydro-3-methyl-(benzo-1,3-thiazol-2-yl)-methylidene)-1-phenylquinolinium iodide] is a fluorescent dye used in studies of yeast and other fungi to monitor cell viability in the research lab and to assay for active fungal infection in the clinical setting. When the plasma membrane is intact, fungal cells internalize FUN-1 and the dye is seen as diffuse green cytosolic fluorescence. FUN-1 is then transported to the vacuole in metabolically active wild type cells and subsequently is compacted into fluorescent red cylindrical intravacuolar structures (CIVS) by an unknown transport pathway. This dye is used to determine yeast viability, as only live cells form CIVS. However, in live Saccharomyces cerevisiae with impaired protein sorting to the yeast vacuole, we report decreased to no CIVS formation, depending on the cellular location of the block in the sorting pathway. Cells with a block in vesicle-mediated transport from the Golgi to prevacuolar compartment (PVC) or with a block in recycling from the PVC to the Golgi demonstrate a substantial impairment in CIVS formation. Instead, the FUN-1 dye is seen either in small punctate structures under fluorescence or as diffuse red cytosol under white light. Thus, researchers using FUN-1 should be cognizant of the limitations of this procedure in determining cell viability as there are viable yeast mutants with impaired CIVS formation.

  20. Toward Synthetic Biology Strategies for Adipic Acid Production: An in Silico Tool for Combined Thermodynamics and Stoichiometric Analysis of Metabolic Networks

    DEFF Research Database (Denmark)

    Averesch, Nils J. H.; Martínez, Verónica S.; Nielsen, Lars K.

    2018-01-01

    Adipic acid, a nylon-6,6 precursor, has recently gained popularity in synthetic biology. Here, 16 different production routes to adipic acid were evaluated using a novel tool for network-embedded thermodynamic analysis of elementary flux modes. The tool distinguishes between thermodynamically...

  1. Quantitative Analysis of Ca, Mg, and K in the Roots of Angelica pubescens f. biserrata by Laser-Induced Breakdown Spectroscopy Combined with Artificial Neural Networks

    Science.gov (United States)

    Wang, J.; Shi, M.; Zheng, P.; Xue, Sh.; Peng, R.

    2018-03-01

    Laser-induced breakdown spectroscopy has been applied for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens Maxim. f. biserrata Shan et Yuan used in traditional Chinese medicine. Ca II 317.993 nm, Mg I 517.268 nm, and K I 769.896 nm spectral lines have been chosen to set up calibration models for the analysis using the external standard and artificial neural network methods. The linear correlation coefficients of the predicted concentrations versus the standard concentrations of six samples determined by the artificial neural network method are 0.9896, 0.9945, and 0.9911 for Ca, Mg, and K, respectively, which are better than for the external standard method. The artificial neural network method also gives better performance comparing with the external standard method for the average and maximum relative errors, average relative standard deviations, and most maximum relative standard deviations of the predicted concentrations of Ca, Mg, and K in the six samples. Finally, it is proved that the artificial neural network method gives better performance compared to the external standard method for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens.

  2. Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses.

    Science.gov (United States)

    Ogawa, Takeshi; Aihara, Takatsugu; Shimokawa, Takeaki; Yamashita, Okito

    2018-04-24

    Creative insight occurs with an "Aha!" experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21-69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

  3. Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model.

    Science.gov (United States)

    Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A; Borst, Jelmer P; Li, Kuncheng

    2016-05-19

    Numerical inductive reasoning refers to the process of identifying and extrapolating the rule involved in numeric materials. It is associated with calculation, and shares the common activation of the fronto-parietal regions with calculation, which suggests that numerical inductive reasoning may correspond to a general calculation process. However, compared with calculation, rule identification is critical and unique to reasoning. Previous studies have established the central role of the fronto-parietal network for relational integration during rule identification in numerical inductive reasoning. The current question of interest is whether numerical inductive reasoning exclusively corresponds to calculation or operates beyond calculation, and whether it is possible to distinguish between them based on the activity pattern in the fronto-parietal network. To directly address this issue, three types of problems were created: numerical inductive reasoning, calculation, and perceptual judgment. Our results showed that the fronto-parietal network was more active in numerical inductive reasoning which requires more exchanges between intermediate representations and long-term declarative knowledge during rule identification. These results survived even after controlling for the covariates of response time and error rate. A computational cognitive model was developed using the cognitive architecture ACT-R to account for the behavioral results and brain activity in the fronto-parietal network.

  4. Significados do trabalho e do dinheiro: Quais suas funções sociais?

    Directory of Open Access Journals (Sweden)

    Sabrina Cavalcanti Barros

    2018-03-01

    Full Text Available Estudos sobre o trabalho e o dinheiro têm enfatizado a dimensão institucional desses fenômenos, destacando funções como a capacidade de interligar a satisfação das necessidades individuais e a manutenção da ordem social. Tais funções são ativadas no cotidiano dos indivíduos, sendo construídas socialmente na produção dos significados dos referidos fenômenos. Exploramos as funções que os significados do trabalho e do dinheiro cumpriram na vida dos operários da construção civil. Realizamos entrevistas semiestruturadas com 44 operários e desenvolvemos análise de conteúdo temática. Identificamos dois grandes eixos norteadores: inclusão e inserção sociais versus exclusão social e realização e sentido de utilidade versus degradação. Os resultados indicaram que as condições de trabalho precárias e a escassez de dinheiro estruturaram os modos de enfrentamento dessas realidades, na valorização dos benefícios alcançados, na naturalização e no conformismo, decorrentes da dureza e limitação de oportunidades experimentadas por esses trabalhadores. Limitações da pesquisa e sugestões são apontadas.

  5. On the way to fun an emotion-based approach to successful game design

    CERN Document Server

    Dillon, Roberto

    2010-01-01

    On the Way to Fun outlines a fine framework linking human emotions and instincts to successful game design, blending a theoretical framework with keys to analyzing game play. The framework is then applied to both successful and unsuccessful games to make for a fine survey for any who want to properly design and develop ideas to maximum benefit.-Midwest Book Review, January 2011I love the '6-11 Framework'. It's a brilliant analysis. Wish I'd thought of it. Emotion is essential to establishing a deep connection with games. So many games lack it, and this book shows the way. The analyses of retro

  6. Uncertainty Quantification of the FUN3D-Predicted NASA CRM Flutter Boundary

    Science.gov (United States)

    Stanford, Bret K.; Massey, Steven J.

    2017-01-01

    A nonintrusive point collocation method is used to propagate parametric uncertainties of the flexible Common Research Model, a generic transport configuration, through the unsteady aeroelastic CFD solver FUN3D. A range of random input variables are considered, including atmospheric flow variables, structural variables, and inertial (lumped mass) variables. UQ results are explored for a range of output metrics (with a focus on dynamic flutter stability), for both subsonic and transonic Mach numbers, for two different CFD mesh refinements. A particular focus is placed on computing failure probabilities: the probability that the wing will flutter within the flight envelope.

  7. Fun City

    DEFF Research Database (Denmark)

    Once the blues guitarist B.B. King sang that when he "didn't wanna live no more", he would go shopping instead. Now, however, shopping has become a lifestyle... The city of today has become "Disneyfied" and "Tivolized". It has become a scene for events. The aim of the book is to encircle and pin ...

  8. FUN CITY

    DEFF Research Database (Denmark)

    Once the blues guitarist B.B. King sang that when he "didn't wanna live no more", he would go shopping instead. Now, however, shopping has become a lifestyle... The city of today has become "Disneyfied" and "Tivolized". It has become a scene for events. The aim of the book is to encircle and pin ...

  9. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility

    DEFF Research Database (Denmark)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail Anne

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements....... A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech......, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where...

  10. Optimization of combination chemotherapy based on the calculation of network entropy for protein-protein interactions in breast cancer cell lines

    Directory of Open Access Journals (Sweden)

    Carels Nicolas

    2015-12-01

    We propose several novel drug combinations using only the approved drugs for the inactivation of the target identified in this study with the purpose of increasing patient survival and lowering the deleterious side effects of cancer chemotherapy.

  11. Nepal Networking

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    , as a Danida fellow. Today, the older sister works in Nepal and the younger in Seattle, where they still make use of their personal networks including connections to their fellow alumni of technical assistance courses. Inspired by work on social remittances in combination with network theory , I argue......Technical Assistance courses have many functions apart from disseminating knowledge and information, one such function is to engender networks. During the course period, participants meet and establish contact and some of these contacts remain connections between alumni for many years after...... the courses are finished. The alumni networks depend on the uses they are put to by the individual alumni and the support they get from alumni and host countries. The United Nations initiated technical assistance courses in the late 1940s in order to train nationals from developing countries as a means...

  12. Acupuncture Induces Time-Dependent Remodelling Brain Network on the Stable Somatosensory First-Ever Stroke Patients: Combining Diffusion Tensor and Functional MR Imaging

    Directory of Open Access Journals (Sweden)

    Lijun Bai

    2014-01-01

    Full Text Available Different treatment interventions induce distinct remodelling of network architecture of entire motor system. Acupuncture has been proved to be of a promising efficacy in motor recovery. However, it is still unclear whether the reorganization of motor-related brain network underlying acupuncture is related with time since stroke and severity of deficit at baseline. The aim of study was to characterize the relation between motor-related brain organization following acupuncture and white matter microstructural changes at an interval of two weeks. We demonstrated that acupuncture induced differential reorganization of motor-related network for stroke patients as time-lapse since stroke. At the baseline, acupuncture can induce the increased functional connectivity between the left primary motor cortex (M1 and the right M1, premotor cortex, supplementary motor area (SMA, thalamus, and cerebellum. After two-week recovery, the increased functional connectivity of the left M1 was more widely distributed and primarily located in the insula, cerebellum, basal ganglia, and SMA. Furthermore, a significant negative relation existed between the FA value in the left M1 at the baseline scanning and node centrality of this region following acupuncture for both baseline and two-week recovery. Our findings may shed a new insight on understanding the reorganization of motor-related theory underlying motor impairments after brain lesions in stroke patients.

  13. Empathy and well-being correlate with centrality in different social networks.

    Science.gov (United States)

    Morelli, Sylvia A; Ong, Desmond C; Makati, Rucha; Jackson, Matthew O; Zaki, Jamil

    2017-09-12

    Individuals benefit from occupying central roles in social networks, but little is known about the psychological traits that predict centrality. Across four college freshman dorms ( n = 193), we characterized individuals with a battery of personality questionnaires and also asked them to nominate dorm members with whom they had different types of relationships. This revealed several social networks within dorm communities with differing characteristics. In particular, additional data showed that networks varied in the degree to which nominations depend on ( i ) trust and ( ii ) shared fun and excitement. Networks more dependent upon trust were further defined by fewer connections than those more dependent on fun. Crucially, network and personality features interacted to predict individuals' centrality: people high in well-being (i.e., life satisfaction and positive emotion) were central to networks characterized by fun, whereas people high in empathy were central to networks characterized by trust. Together, these findings provide network-based corroboration of psychological evidence that well-being is socially attractive, whereas empathy supports close relationships. More broadly, these data highlight how an individual's personality relates to the roles that they play in sustaining their community.

  14. Modularization and Validation of FUN3D as a CREATE-AV Helios Near-Body Solver

    Science.gov (United States)

    Jain, Rohit; Biedron, Robert T.; Jones, William T.; Lee-Rausch, Elizabeth M.

    2016-01-01

    Under a recent collaborative effort between the US Army Aeroflightdynamics Directorate (AFDD) and NASA Langley, NASA's general unstructured CFD solver, FUN3D, was modularized as a CREATE-AV Helios near-body unstructured grid solver. The strategies adopted in Helios/FUN3D integration effort are described. A validation study of the new capability is performed for rotorcraft cases spanning hover prediction, airloads prediction, coupling with computational structural dynamics, counter-rotating dual-rotor configurations, and free-flight trim. The integration of FUN3D, along with the previously integrated NASA OVERFLOW solver, lays the ground for future interaction opportunities where capabilities of one component could be leveraged with those of others in a relatively seamless fashion within CREATE-AV Helios.

  15. Avaliação da função renal do idoso em duas horas

    OpenAIRE

    Benarab,Maria do Carmo B. Sammartino; Castiglia,Yara Marcondes Machado; Vianna,Pedro Thadeu Galvão; Braz,José Reinaldo Cerqueira

    2005-01-01

    JUSTIFICATIVA E OBJETIVOS: Os idosos têm diminuição progressiva da função renal e os hipertensos, maior risco de lesão renal adicional no intra-operatório. Avalia-se a função renal pela depuração da creatinina, com débito urinário de 24 horas, para diluir o erro de possível volume vesical residual (VVR). O objetivo deste trabalho foi avaliar a função renal pré-operatória de idosos hipertensos e não-hipertensos, com débito urinário de duas horas, utilizando aparelho de ultra-som portátil para ...

  16. O sujeito psicótico e a função do delírio

    OpenAIRE

    Briggs, Raquel; Rinaldi, Doris

    2014-01-01

    Este trabalho aborda o conceito de delírio e sua função na estrutura psicótica. A psicanálise considera o delírio, por um lado, fenômeno elementar e, por outro, tentativa de cura, portador de uma verdade. O presente trabalho objetiva abordar a estruturação delirante, assim como a função da mesma para o sujeito paranoico, no sentido de situar a direção de tratamento na clínica da paranoia. A partir de um caso clínico e embasando-se nos conceitos da psicanálise, discute-se a função do mesmo par...

  17. Código Florestal, função socioambiental da terra e soberania alimentar

    Directory of Open Access Journals (Sweden)

    Sérgio Sauer

    Full Text Available O presente artigo tem como objetivo discutir alterações do Código Florestal, especialmente aspropostas de mudanças nas noções de Reserva Legal e Área de Preservação Permanente (APP, em processo de rediscussão no Congresso, após sanção presidencial com vetos no texto aprovado na Câmara em 25 de abril de 2012. Para suprir lacunas da nova Lei, o Executivo Federal editou a Medida Provisória (MP 571/2012, que retoma a discussão da matéria. Tanto dispositivos da nova Lei como alterações propostas ao texto da MP geram insegurança alimentar e visam a eliminar a função socioambiental da terra. A motivação das mudanças não está relacionada à sustentabilidade ambiental ou às mudanças climáticas, temas fundamentais na agenda mundial, mas parte do princípio de que a natureza é um empecilho ao desenvolvimento. Este artigo resgata as principais alterações no Código Florestal relacionadas à Reserva Legal e às APPs, estabelecendo relações (impactos negativos com a função socioambiental da terra e a soberania alimentar.

  18. An understanding of Japanese children's perceptions of fun, barriers, and facilitators of active free play.

    Science.gov (United States)

    Lee, YingHua; Takenaka, Koji; Kanosue, Kazuyuki

    2015-09-01

    Physical activity contributes to children's physical and mental well-being. Research suggests that active free play helps to maintain and increase physical activity in children and also contributes to social and emotional well-being. To date, these studies have focused on Western countries. Thus, this study was conducted to gain insights into the factors of perceptions of fun, barriers, and facilitators affecting active free play from the perspective of Japanese children using focus group interviews. In Japan, 12 focus groups were conducted with 60 children aged 9-11 years. Children's perceptions of fun in active free play were categorized into socializing, achievement, emotions, and freedom. Additionally, active boys' groups were interested in free play and adventure play; girls' groups were interested in free play with less physical movement and challenges; inactive boys' groups were interested in relaxing and competitive play with bodily contact. However, children mentioned that busy schedules, weather, and health-related factors acted as main barriers. Lastly, children noted facilitators include setting schedules, having access to equipment and playgrounds, and holding special events. The findings provide insights into active free play-related factors for active and inactive Japanese children and also clarify the differences between Japanese and Western children. Such findings will contribute to designing interventions to increase active free play. © The Author(s) 2013.

  19. Radiation Coupling with the FUN3D Unstructured-Grid CFD Code

    Science.gov (United States)

    Wood, William A.

    2012-01-01

    The HARA radiation code is fully-coupled to the FUN3D unstructured-grid CFD code for the purpose of simulating high-energy hypersonic flows. The radiation energy source terms and surface heat transfer, under the tangent slab approximation, are included within the fluid dynamic ow solver. The Fire II flight test, at the Mach-31 1643-second trajectory point, is used as a demonstration case. Comparisons are made with an existing structured-grid capability, the LAURA/HARA coupling. The radiative surface heat transfer rates from the present approach match the benchmark values within 6%. Although radiation coupling is the focus of the present work, convective surface heat transfer rates are also reported, and are seen to vary depending upon the choice of mesh connectivity and FUN3D ux reconstruction algorithm. On a tetrahedral-element mesh the convective heating matches the benchmark at the stagnation point, but under-predicts by 15% on the Fire II shoulder. Conversely, on a mixed-element mesh the convective heating over-predicts at the stagnation point by 20%, but matches the benchmark away from the stagnation region.

  20. Provas da função pulmonar. Controlo de qualidade. Aspectos gerais (1a Parte

    Directory of Open Access Journals (Sweden)

    J.M. Reis Ferreira

    1999-07-01

    Full Text Available RESUMO: Os autores procuraram neste artigo sensibilizar todos os que lidam de perto com a realização dos testes da função respiratória, para a importância da qualidade e dos meios disponiveis para conseguir o seu controlo. Foram deste modo encarados os diferentes factores intervenientes na qualidade, analisandoos de acordo com os dados fornecidos fundamentalmente pela experiência. Foram assim focados, neste primeiro artigo, apenas aspectos gerais trazidos pela prática do dia a dia, a que se seguirá a publicação de novo texto em que serão, dentro do mesmo âmbito, encaradas as diferentes técnicas actualmente usadas para a avaliação da Função Respiratória.REV PORT PNEUMOL 1999; V (4: 393-404 ABSTRACT: The authors claim for the importance of the quality control in order to assure clinically useful results and a well-functioning lung function laboratory, and analyse briefly the different general factors that could be involved in the lack of quality.REV PORTPNEUMOL 1999; V (4: 393-404 Key-words: Quality control, Equipment, Calibration, Accuracity, Colaboration, Palavras-chave: Controlo de qualidade, Equipamento, Calibração, Precisão, Exactidão;Colaboração

  1. Does the Animal Fun program improve motor performance in children aged 4-6 years?

    Science.gov (United States)

    Piek, J P; McLaren, S; Kane, R; Jensen, L; Dender, A; Roberts, C; Rooney, R; Packer, T; Straker, L

    2013-10-01

    The Animal Fun program was designed to enhance the motor ability of young children by imitating the movements of animals in a fun, inclusive setting. The efficacy of this program was investigated through a randomized controlled trial using a multivariate nested cohort design. Pre-intervention scores were recorded for 511 children aged 4.83 years to 6.17 years (M=5.42 years, SD=3.58 months). Six control and six intervention schools were compared 6 months later following the intervention, and then again at 18 months after the initial testing when the children were in their first school year. Changes in motor performance were examined using the Bruininks-Oseretsky Test of Motor Proficiency short form. Data were analyzed using multi-level-mixed effects linear regression. A significant Condition×Time interaction was found, F(2,1219)=3.35, p=.035, demonstrating that only the intervention group showed an improvement in motor ability. A significant Sex×Time interaction was also found, F(2,1219)=3.84, p=.022, with boys improving over time, but not girls. These findings have important implications for the efficacy of early intervention of motor skills and understanding the differences in motor performance between boys and girls. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Developing the fun and educative module in plant morphology and anatomy learning for tenth graders

    Directory of Open Access Journals (Sweden)

    Alfi Suciyati

    2018-03-01

    Full Text Available This research aims to examine the eligibility of and responses from expert media, expert material, practitioners and students’ on the ‘Fun and Educative’ biology module. The module was developed in a fun and educative way presenting various educative games. The research development model is using ADDIE model that consists of five phases: Analysis, Design, Development, Implementation, and Evaluation. The data collection technique employed examination of learning media experts, material experts, practitioners (biology teachers, and students. The data of research was analyzed in descriptive-qualitative and descriptive-qualitative ways. The results of evaluation on the module’s eligibility convey that the learning media expert gave 87.69% with the category of ‘highly eligible’, the material expert gave 86.00% with the category of ‘highly eligible', and the practitioners gave 83.68% with the category of ‘eligible'. The students' responses to questionnaires given related to the developed module gave 90.00% with the category of ‘highly interesting'. Based on the results of examination by the media expert, material expert, practitioners, and students, conclude that the module has fulfilled the criteria of good and eligible learning material and can be used for studying biology.

  3. Zeros da função zeta de Riemann e o teorema dos números primos

    OpenAIRE

    Oliveira, Willian Diego [UNESP

    2013-01-01

    We studied various properties of the Riemann’s zeta function. Three proofs of the Prime Number Theorem were provides. Classical results on zero-free region of the zeta function, as well as their relation to the error term in the Prime Number Theorem, were studied in details Estudamos várias propriedades da função zeta de Riemann. Três provas do Teorema dos Números Primos foram fornecidas. Resultados clássicos sobre regiões livres de zeros da função zeta, bem como sua relação com o termo do...

  4. Uma análise comparativa de funções MDX nos servidores Analysis Services e Mondrian

    OpenAIRE

    ALBUQUERQUE, Erivam Anselmo de

    2013-01-01

    A MultiDimensional eXpression (MDX) é uma linguagem de consulta para processamento analítico de dados ou On-line Analytical Processing (OLAP). Apesar de esta linguagem ser usada pela maioria dos servidores OLAP, esta não é um padrão de direito. Portanto, tem-se pouca (ou nenhuma) garantia de que as funções MDX usadas por um servidor OLAP também possam ser usadas em outros servidores. Neste contexto, de forma a comparar as funções MDX de um servidor OLAP de código aberto e outro de código fech...

  5. B-jet and c-jet identification with Neural Networks as well as combination of multivariate analyses for the search for of multivariate analyses for the search for single top-quark production

    International Nuclear Information System (INIS)

    Renz, Manuel

    2008-01-01

    half. In the second part of this diploma thesis, a method for the combination of three multivariate single-top analyses using an integrated luminosity of 2.2 fb -1 is presented. For this purpose the discriminants of the Likelihood Function analysis, the Matrix Element method and the Neural Network analysis are used as input variables to a neural network. Overall four different networks are trained, one for events with two or three jets and one or two SecVtx tags, respectively. Using a binned likelihood function, the outputs of these networks are fitted to the output distribution of observed events. A single top-quark production cross section of σ single-top = 2.2 -0.7 +0.8 pb is measured. Ensemble tests are performed for the calculation of the sensitivity and observed significance, which are found to be 4.8σ and 3.9σ, respectively. Hence the improvement of this combination is roughly 8% in comparison with sensitivities found by the individual analyses. Due to the proportionality of σ single-top and |V tb | 2 and under the assumption V tb >> V ts , V td , a value for |V tb | is quoted: |V tb | = 0.88 -0.12 +0.14 (exp.) ± 0.07(theo.). It can be seen, that the given uncertainties are too large for a verification or falsification of the unitarity assumption of the CKM-matrix. Parallel to this combination a further combination method (NEAT-combination) has been developed. This combination uses a neural network trained with a neuroevolution technique, which optimizes the neural network architecture and weights through the use of genetic algorithms. In this analysis an improvement of roughly 12% could be reached. In figure 7.1 the current situation for the measurement of the single top-quark production cross section is summarized. After collecting more data, CDF will be able to observe single top-quark production with a significance larger than 5.0σ. Nevertheless, the cross section measurement will still have large uncertainties on the level of 20%. Precise measurements

  6. B-jet and c-jet identification with Neural Networks as well as combination of multivariate analyses for the search for of multivariate analyses for the search for single top-quark production

    Energy Technology Data Exchange (ETDEWEB)

    Renz, Manuel; /Karlsruhe U., EKP

    2008-06-01

    into half. In the second part of this diploma thesis, a method for the combination of three multivariate single-top analyses using an integrated luminosity of 2.2 fb{sup -1} is presented. For this purpose the discriminants of the Likelihood Function analysis, the Matrix Element method and the Neural Network analysis are used as input variables to a neural network. Overall four different networks are trained, one for events with two or three jets and one or two SecVtx tags, respectively. Using a binned likelihood function, the outputs of these networks are fitted to the output distribution of observed events. A single top-quark production cross section of {sigma}{sub single-top} = 2.2{sub -0.7}{sup +0.8} pb is measured. Ensemble tests are performed for the calculation of the sensitivity and observed significance, which are found to be 4.8{sigma} and 3.9{sigma}, respectively. Hence the improvement of this combination is roughly 8% in comparison with sensitivities found by the individual analyses. Due to the proportionality of {sigma}{sub single-top} and |V{sub tb}|{sup 2} and under the assumption V{sub tb} >> V{sub ts}, V{sub td}, a value for |V{sub tb}| is quoted: |V{sub tb}| = 0.88{sub -0.12}{sup +0.14}(exp.) {+-} 0.07(theo.). It can be seen, that the given uncertainties are too large for a verification or falsification of the unitarity assumption of the CKM-matrix. Parallel to this combination a further combination method (NEAT-combination) has been developed. This combination uses a neural network trained with a neuroevolution technique, which optimizes the neural network architecture and weights through the use of genetic algorithms. In this analysis an improvement of roughly 12% could be reached. In figure 7.1 the current situation for the measurement of the single top-quark production cross section is summarized. After collecting more data, CDF will be able to observe single top-quark production with a significance larger than 5.0{sigma}. Nevertheless, the cross

  7. Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

    Science.gov (United States)

    Adams, Matthew D; Kanaroglou, Pavlos S

    2016-03-01

    Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved

  8. Biomarkers of Treatment Toxicity in Combined-Modality Cancer Therapies with Radiation and Systemic Drugs: Study Design, Multiplex Methods, Molecular Networks

    Directory of Open Access Journals (Sweden)

    Anne Hansen Ree

    2014-12-01

    Full Text Available Organ toxicity in cancer therapy is likely caused by an underlying disposition for given pathophysiological mechanisms in the individual patient. Mechanistic data on treatment toxicity at the patient level are scarce; hence, probabilistic and translational linkages among different layers of data information, all the way from cellular targets of the therapeutic exposure to tissues and ultimately the patient’s organ systems, are required. Throughout all of these layers, untoward treatment effects may be viewed as perturbations that propagate within a hierarchically structured network from one functional level to the next, at each level causing disturbances that reach a critical threshold, which ultimately are manifested as clinical adverse reactions. Advances in bioinformatics permit compilation of information across the various levels of data organization, presumably enabling integrated systems biology-based prediction of treatment safety. In view of the complexity of biological responses to cancer therapy, this communication reports on a “top-down” strategy, starting with the systematic assessment of adverse effects within a defined therapeutic context and proceeding to transcriptomic and proteomic analysis of relevant patient tissue samples and computational exploration of the resulting data, with the ultimate aim of utilizing information from functional connectivity networks in evaluation of patient safety in multimodal cancer therapy.

  9. Impact of LABA/LAMA combination on exercise endurance and lung hyperinflation in COPD: A pair-wise and network meta-analysis.

    Science.gov (United States)

    Calzetta, Luigino; Ora, Josuel; Cavalli, Francesco; Rogliani, Paola; O'Donnell, Denis E; Cazzola, Mario

    2017-08-01

    The ability to exercise is an important clinical outcome in COPD, and the improvement in exercise capacity is recognized to be an important goal in the management of COPD. Therefore, since the current interest in the use of bronchodilators in COPD is gradually shifting towards the dual bronchodilation, we carried out a meta-analysis to evaluate the impact of LABA/LAMA combination on exercise capacity and lung hyperinflation in COPD. RCTs were identified after a search in different databases of published and unpublished trials. The aim of this study was to assess the influence of LABA/LAMA combinations on endurance time (ET) and inspiratory capacity (IC), vs. monocomponents. Eight RCTs including 1632 COPD patients were meta-analysed. LABA/LAMA combinations were significantly (P meta-analysis. This meta-analysis clearly demonstrates that if the goal of the therapy is to enhance exercise capacity in patients with COPD, LABA/LAMA combinations consistently meet the putative clinically meaningful differences for both ET and IC and, in this respect, are superior to their monocomponents. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Modelos de distribuição de diâmetros utilizando a função log gama

    Directory of Open Access Journals (Sweden)

    Daniel Henrique Breda Binoti

    2013-03-01

    Full Text Available Objetivou-se neste estudo avaliar a eficiência da função log gama para a descrição da estrutura diamétrica de povoamentos equiâneos, bem como propor um modelo de distribuição diamétrica utilizando esta função. A função foi ajustada a dados de parcelas permanentes de inventário, mensuradas em seis idades. A aderência da função aos dados foi comprovada pelo teste Kolmogorov-Smirnov. A análise gráfica de resíduos não apresentou tendenciosidade para os modelos construídos. A função log gama pode ser utilizada para a construção de modelos de distribuição diamétrica de eucalipto.

  11. Improving health-related fitness in children: the fit-4-Fun randomized controlled trial study protocol

    Directory of Open Access Journals (Sweden)

    Eather Narelle

    2011-12-01

    Full Text Available Abstract Background Declining levels of physical fitness in children are linked to an increased risk of developing poor physical and mental health. Physical activity programs for children that involve regular high intensity physical activity, along with muscle and bone strengthening activities, have been identified by the World Health Organisation as a key strategy to reduce the escalating burden of ill health caused by non-communicable diseases. This paper reports the rationale and methods for a school-based intervention designed to improve physical fitness and physical activity levels of Grades 5 and 6 primary school children. Methods/Design Fit-4-Fun is an 8-week multi-component school-based health-related fitness education intervention and will be evaluated using a group randomized controlled trial. Primary schools from the Hunter Region in NSW, Australia, will be invited to participate in the program in 2011 with a target sample size of 128 primary schools children (age 10-13. The Fit-4-Fun program is theoretically grounded and will be implemented applying the Health Promoting Schools framework. Students will participate in weekly curriculum-based health and physical education lessons, daily break-time physical activities during recess and lunch, and will complete an 8-week (3 × per week home activity program with their parents and/or family members. A battery of six health-related fitness assessments, four days of pedometery-assessed physical activity and a questionnaire, will be administered at baseline, immediate post-intervention (2-months and at 6-months (from baseline to determine intervention effects. Details of the methodological aspects of recruitment, inclusion criteria, randomization, intervention program, assessments, process evaluation and statistical analyses are described. Discussion The Fit-4-Fun program is an innovative school-based intervention targeting fitness improvements in primary school children. The program will

  12. Improving health-related fitness in children: the Fit-4-Fun randomized controlled trial study protocol.

    Science.gov (United States)

    Eather, Narelle; Morgan, Philip J; Lubans, David R

    2011-12-05

    Declining levels of physical fitness in children are linked to an increased risk of developing poor physical and mental health. Physical activity programs for children that involve regular high intensity physical activity, along with muscle and bone strengthening activities, have been identified by the World Health Organisation as a key strategy to reduce the escalating burden of ill health caused by non-communicable diseases. This paper reports the rationale and methods for a school-based intervention designed to improve physical fitness and physical activity levels of Grades 5 and 6 primary school children. Fit-4-Fun is an 8-week multi-component school-based health-related fitness education intervention and will be evaluated using a group randomized controlled trial. Primary schools from the Hunter Region in NSW, Australia, will be invited to participate in the program in 2011 with a target sample size of 128 primary schools children (age 10-13). The Fit-4-Fun program is theoretically grounded and will be implemented applying the Health Promoting Schools framework. Students will participate in weekly curriculum-based health and physical education lessons, daily break-time physical activities during recess and lunch, and will complete an 8-week (3 × per week) home activity program with their parents and/or family members. A battery of six health-related fitness assessments, four days of pedometery-assessed physical activity and a questionnaire, will be administered at baseline, immediate post-intervention (2-months) and at 6-months (from baseline) to determine intervention effects. Details of the methodological aspects of recruitment, inclusion criteria, randomization, intervention program, assessments, process evaluation and statistical analyses are described. The Fit-4-Fun program is an innovative school-based intervention targeting fitness improvements in primary school children. The program will involve a range of evidence-based behaviour change strategies to

  13. Marcadores práticos de função renal em pacientes com cistinose

    Directory of Open Access Journals (Sweden)

    Luciana Pache de Faria Guimaraes

    2012-09-01

    Full Text Available INTRODUÇÃO: Cistinose é uma doença sistêmica, autossômica recessiva, que leva à insuficiência renal crônica na infância, a não ser que o tratamento com cisteamina seja iniciado precocemente. Mesmo nestas condições, os pacientes evoluem para doença renal crônica terminal por volta da segunda década da vida. Portanto, a avaliação da função renal é essencial neste grupo de pacientes. OBJETIVO: Avaliar e correlacionar a cistatina C, creatinina sérica e o clearance de creatinina pela Fórmula de Schwartz em pacientes com cistinose, com diferentes graus de função renal. MÉTODOS: Foram incluídos pacientes com menos de 18 anos de idade, com diferentes níveis de função renal, de acordo com o KDOQI em estágios 1 a 4. Nenhum dos pacientes estava em terapia de substituição renal. Foram medidos os seguintes parâmetros: cistatina C, creatinina sérica e o clearance de creatinina pela fórmula de Schwartz. RESULTADOS: Foram analisadas 103 amostras de sangue de 26 pacientes. Foi detectada correlação significativa entre creatinina sérica e cistatina C (r = 0,81, p < 0,0001, cistatina C e o clearance de creatinina pela fórmula de Schwartz (r = -0,84, p < 0,0001 e creatinina sérica e clearance de creatinina (r = -0,97, p < 0,0001. CONCLUSÕES: A medida da cistatina não mostrou nenhuma vantagem sobre a creatinina sérica e o clearance de creatinina pela fórmula de Schwartz em pacientes com cistinose para avaliar o ritmo de filtração glomerular. Este é o primeiro relato sobre o valor da creatinina sérica, do clearance de creatinina pela fórmula de Schwartz e da cistatina C em pacientes com cistinose.

  14. Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling

    Directory of Open Access Journals (Sweden)

    Craigon Marie

    2009-08-01

    Full Text Available Abstract Background Interferons (IFNs are potent antiviral cytokines capable of reprogramming the macrophage phenotype through the induction of interferon-stimulated genes (ISGs. Here we have used targeted RNA interference to suppress the expression of a number of key genes associated with IFN signalling in murine macrophages prior to stimulation with interferon-gamma. Genome-wide changes in transcript abundance caused by siRNA activity were measured using exon-level microarrays in the presence or absence of IFNγ. Results Transfection of murine bone-marrow derived macrophages (BMDMs with a non-targeting (control siRNA and 11 sequence-specific siRNAs was performed using a cationic lipid transfection reagent (Lipofectamine2000 prior to stimulation with IFNγ. Total RNA was harvested from cells and gene expression measured on Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. Network-based analysis of these data revealed six siRNAs to cause a marked shift in the macrophage transcriptome in the presence or absence IFNγ. These six siRNAs targeted the Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts. The perturbation of the transcriptome by the six siRNAs was highly similar in each case and affected the expression of over 600 downstream transcripts. Regulated transcripts were clustered based on co-expression into five major groups corresponding to transcriptional networks associated with the type I and II IFN response, cell cycle regulation, and NF-KB signalling. In addition we have observed a significant non-specific immune stimulation of cells transfected with siRNA using Lipofectamine2000, suggesting use of this reagent in BMDMs, even at low concentrations, is enough to induce a type I IFN response. Conclusion Our results provide evidence that the type I IFN response in murine BMDMs is dependent on Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2, and that siRNAs targeted to these genes results in perturbation of key transcriptional networks associated

  15. Games as Actors - Interaction, Play, Design, and Actor Network Theory

    DEFF Research Database (Denmark)

    Jessen, Jari Due; Jessen, Carsten

    2014-01-01

    When interacting with computer games, users are forced to follow the rules of the game in return for the excitement, joy, fun, or other pursued experiences. In this paper, we investigate how games a chieve these experiences in the perspective of Actor Network Theory (ANT). Based on a qualitative......, and by doing so they create in humans what in modern play theory is known as a “state of play”...

  16. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

    Science.gov (United States)

    Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

    2015-07-28

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

  17. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

    Energy Technology Data Exchange (ETDEWEB)

    Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

    2016-10-25

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

  18. Medusa-Isosampler: A modular, network-based observatory system for combined physical, chemical and microbiological monitoring, sampling and incubation of hydrothermal and cold seep fluids

    Science.gov (United States)

    Schultz, A.; Flynn, M.; Taylor, P.

    2004-12-01

    The study of life in extreme environments provides an important context from which we can undertake the search for extraterrestrial life, and through which we can better understand biogeochemical feedback in terrestrial hydrothermal and cold seep systems. The Medusa-Isosampler project is aimed at fundamental research into understanding the potential for, and limits to, chemolithoautotrophic life, i.e. primary production without photosynthesis. One environment that might foster such life is associated with the high thermal and chemical gradient environment of hydrothermal vent structures. Another is associated with the lower thermal and chemical gradient environment of continental margin cold seeps. Under NERC, NASA and industrial support, we have designed a flexible instrumentation system, operating as networked, autonomous modules on a local area network, that will make possible simultaneous physical and chemical sampling and monitoring of hydrothermal and cold seep fluids, and the in situ and laboratory incubation of chemosynthetic microbes under high pressure, isobaric conditions. The system has been designed with long-term observatory operations in mind, and may be reconfigured dynamically as the requirements of the observatory installation change. The modular design will also accommodate new in situ chemical and biosensor technologies, provided by third parties. The system may be configured for seafloor use, and can be adapted to use in IODP boreholes. Our overall project goals are provide an instrumentation system capable of probing both high and low-gradient water-rock systems for chemolithoautotrophic biospheres, to identify the physical and chemical conditions that define these microhabitats and explore the details of the biogeochemical feedback loops that mediate these microhabitats, and to attempt to culture and identify chemolithoautotrophic microbial communities that might exist there. The Medusa-Isosampler system has been produced and is now

  19. Comparison of palbociclib in combination with letrozole or fulvestrant with endocrine therapies for advanced/metastatic breast cancer: network meta-analysis.

    Science.gov (United States)

    Chirila, Costel; Mitra, Debanjali; Colosia, Ann; Ling, Caroline; Odom, Dawn; Iyer, Shrividya; Kaye, James A

    2017-08-01

    Palbociclib is the first cyclin-dependent kinase 4/6 inhibitor approved in the United States for HR+/HER2- advanced/metastatic breast cancer, in combination with letrozole as initial endocrine-based therapy in postmenopausal women or with fulvestrant in women with disease progression following endocrine therapy. We compared progression-free survival (PFS) and discontinuations due to adverse events for palbociclib combinations against other endocrine therapies using a mixed-treatment comparison meta-analysis of randomized, controlled trials. A systematic literature review identified relevant trials. Separate analyses were conducted for each palbociclib combination using a Bayesian approach. Treatment rankings were established using the surface under the cumulative ranking curve (SUCRA). Sixty-five unique studies met inclusion criteria. Palbociclib plus letrozole had the highest SUCRA value (99.9%) and was associated with significantly longer PFS than all comparators in treatment-naïve patients (hazard ratios [HRs] ranged from 0.41 to 0.58). Palbociclib plus fulvestrant had the second highest SUCRA value (93.9%) and, in previously treated patients, yielded significantly longer PFS than most comparators (HRs ranged from 0.26 to 0.46); the exception was everolimus plus exemestane, with similar PFS (HR, 1.04; 95% credible interval [CrI], 0.58-1.76). Palbociclib plus fulvestrant was associated with significantly lower odds of discontinuation due to adverse events than everolimus plus exemestane (odds ratio, 0.14; 95% CrI, 0.05-0.39). The results suggest that the two palbociclib combinations yielded significantly greater PFS than endocrine therapy in treatment-naïve and previously treated patients with advanced/metastatic breast cancer. Palbociclib plus fulvestrant was associated with significantly less toxicity than everolimus plus exemestane.

  20. HealthLines: Quick Tips for Seasonal Health, Safety and Fun... "Ah, when the sun beats down…"

    Science.gov (United States)

    ... Current Issue Past Issues HealthLines: Quick Tips for Seasonal Health, Safety and Fun Past Issues / Spring 2007 ... and protect against reflected UV radiation (from sand, water, or snow). UV radiation ... and stress fractures. Remember safety gear. Depending on the sport, ...

  1. Fun & Fit, Phase I: A Program for Overweight African American and Hispanic American Children from Low-Income Families

    Science.gov (United States)

    Meaney, Karen S.; Hart, Melanie A.; Griffin, L. Kent

    2009-01-01

    Fun & Fit is a program designed to create positive physical activity experiences and to promote healthy lifestyle choices among overweight children from low-income African American and Hispanic American families. The program is a collaborative project between Texas Tech University and the Lubbock Independent School District funded through a…

  2. MODEL PENGEMBANGAN PERMAINAN FUN HOCKEY PADA SISWA KELAS XI SMA NEGERI 1 BAWANG KECAMATAN BAWANG KABUPATEN BATANG TAHUN 2014.

    Directory of Open Access Journals (Sweden)

    Wahyu Putri Vembriana Dewi

    2015-07-01

    Full Text Available The purpose of this study was to produce a model of the development of the game Fun Hockey in the XI student class of SMAN 1 Bawang, Bawang Subdistrict, Batang. The method used is the development of Borg & Gall, namely: (1 to analyze the products that will be developed that are obtained from the information collection, including field observations and study of literature, (2 develop a form of initial product model game Fun Hockey, (3 expert validation test which uses a physical education expert (hockey skills and learning experts physical education in high school, as well as small scale test, using questionnaires and consultations later in the analysis, (4 the first product revision, revision of the product based on the results of expert evaluation and testing of small-scale (12 students, (5 field trials (28 students, (6 the revision of the final product is done based on the results of field trials, (7 the outcome Fun Hockey game for students of XI class generated through the revision of field trials. From the data on the differences can concluded that the Fun Hockey Game model development can be implemented as an alternative model for students learning physical education XI class SMAN 1 Bawang, Bawang Subdistrict, Batang.

  3. Predictive power of task orientation, general self-efficacy and self-determined motivation on fun and boredom

    Directory of Open Access Journals (Sweden)

    Lorena Ruiz-González

    2015-12-01

    Full Text Available Abstract The aim of this study was to test the predictive power of dispositional orientations, general self-efficacy and self-determined motivation on fun and boredom in physical education classes, with a sample of 459 adolescents between 13 and 18 with a mean age of 15 years (SD = 0.88. The adolescents responded to four Likert scales: Perceptions of Success Questionnaire, General Self-Efficacy Scale, Sport Motivation Scale and Intrinsic Satisfaction Questionnaire in Sport. The results showed the structural regression model showed that task orientation and general self-efficacy positively predicted self-determined motivation and this in turn positively predicted more fun and less boredom in physical education classes. Consequently, the promotion of an educational task-oriented environment where learners perceive their progress and make them feel more competent, will allow them to overcome the intrinsically motivated tasks, and therefore they will have more fun. Pedagogical implications for less boredom and more fun in physical education classes are discussed.

  4. Teaching Case: IS Security Requirements Identification from Conceptual Models in Systems Analysis and Design: The Fun & Fitness, Inc. Case

    Science.gov (United States)

    Spears, Janine L.; Parrish, James L., Jr.

    2013-01-01

    This teaching case introduces students to a relatively simple approach to identifying and documenting security requirements within conceptual models that are commonly taught in systems analysis and design courses. An introduction to information security is provided, followed by a classroom example of a fictitious company, "Fun &…

  5. Using Fun in the Statistics Classroom: An Exploratory Study of College Instructors' Hesitations and Motivations

    Science.gov (United States)

    Lesser, Lawrence M.; Wall, Amitra A.; Carver, Robert H.; Pearl, Dennis K.; Martin, Nadia; Kuiper, Shonda; Posner, Michael A.; Erickson, Patricia; Liao, Shu-Min; Albert, Jim; Weber, John J., III

    2013-01-01

    This study examines statistics instructors' use of fun as well as their motivations, hesitations, and awareness of resources. In 2011, a survey was administered to attendees at a national statistics education conference, and follow-up qualitative interviews were conducted with 16 of those ("N" = 249) surveyed to provide further…

  6. Does the Animal Fun program improve social-emotional and behavioural outcomes in children aged 4-6 years?

    NARCIS (Netherlands)

    Piek, J.P.; Kane, R.; Rigoli, D.; McLaren, S.; Roberts, C.M.; Rooney, R.; Jensen, L.; Dender, A.; Packer, T.L.; Straker, L.

    2015-01-01

    Animal Fun was designed to enhance motor and social development in young children. Its efficacy in improving motor skills was presented previously using a randomised controlled trial and a multivariate nested cohort design. Based on the Environmental Stress Hypothesis, it was argued that the program

  7. A função de controle nos sistemas integrados de manufatura

    Directory of Open Access Journals (Sweden)

    Flavio Cesar F Fernandes

    1991-06-01

    Full Text Available Faz-se uma proposição de vários conceitos atinentes ao gerenciamento da produção, muitos dos quais são válidos também para os Sistemas de Manufatura Convencional, mas que estão aqui colocados dentro do contexto dos Sistemas Integrados de Manufatura (SIMs, que são os sistemas desenvolvidos sob a filosofia de fabricação CIM ('Computer Integrated Manufacturing = Manufatura Integrada por Computador. Mostra-se que a integração depende basicamente da função controle.Manufacturing integration is reviewed and various concepts and definitions founded in literature are presented for conventional and automated manufacturing systems. The survey emphasizes information system management and control importance in order to improve manufacturing functions integration.

  8. Creating Evaluation Profiles for Games Designed to be Fun: An Interpretive Framework for Serious Game Mechanics

    DEFF Research Database (Denmark)

    Ulrich, Frank; Helms, Niels Henrik

    2017-01-01

    Background. Games can be great pedagogical tools for educators and students. COTS games (commercialoff-the-shelf) are designed for the pure purpose of leisure but can also contain educational value. Aim. In this paper, we address the potential of COTS games as serious games. We develop...... an interpretive evaluation framework that can identify the educational value in COTS games. Application. The presented framework can create evaluative profiles of the learning, social, game, and immersive mechanics of COTS games as educational tools. Moreover, the framework can position COTS games between four...... enables critical reflection on the game mechanics; thereby capturing the complexity of the game mechanics that makes COTS game both educational and fun to play....

  9. Efficacy of propidium iodide and FUN-1 stains for assessing viability in basidiospores of Rhizopogon roseolus.

    Science.gov (United States)

    Fernández-Miranda, Elena; Majada, Juan; Casares, Abelardo

    2017-01-01

    The use of spores in applications of ectomycorrhizal fungi requires information regarding spore viability and germination, especially in genera such as Rhizopogon with high rates of spore dormancy. The authors developed a protocol to assess spore viability of Rhizopogon roseolus using four vital stains to quantify spore viability and germination and to optimize storage procedures. They showed that propidium iodide is an excellent stain for quantifying nonviable spores. Observing red fluorescent intravacuolar structures following staining with 2-chloro-4-(2,3-dihydro-3-methyl-(benzo-1,3-thiazol-2-yl)-methylidene)-1-phenylquinolinium iodide (FUN-1) can help identify viable spores that are activated. At 6 mo and 1 y, the spores kept in a water suspension survived better than those left within intact, dry gasterocarps. Our work highlights the importance of temperature, nutrients, and vitamins for maturation and germination of spores of R. roseolus during 1 y of storage.

  10. Marcadores práticos de função renal em pacientes com cistinose

    OpenAIRE

    Guimaraes,Luciana Pache de Faria; Neri,Letícia Aparecida Lopes; Sumita,Nairo Massakasu; Vaisbich,Maria Helena

    2012-01-01

    INTRODUÇÃO: Cistinose é uma doença sistêmica, autossômica recessiva, que leva à insuficiência renal crônica na infância, a não ser que o tratamento com cisteamina seja iniciado precocemente. Mesmo nestas condições, os pacientes evoluem para doença renal crônica terminal por volta da segunda década da vida. Portanto, a avaliação da função renal é essencial neste grupo de pacientes. OBJETIVO: Avaliar e correlacionar a cistatina C, creatinina sérica e o clearance de creatinina pela Fórmula de Sc...

  11. Efeito do transplante renal na morfologia e função cardíaca

    OpenAIRE

    Souza,Francival Leite de; Monteiro Junior,Francisco das Chagas; Salgado Filho,Natalino

    2012-01-01

    O envolvimento cardíaco é muito frequente nos portadores de doença renal crônica em diálise. O transplante renal resulta em redução da morbidade e mortalidade em relação aos pacientes em diálise. O objetivo desta revisão foi abordar o efeito do transplante renal na estrutura e função cardíaca avaliada pela ecodopplercardiografia. Desde a década de 1980, os estudos já demonstravam tendência à melhora nos parâmetros cardíacos após o transplante renal. Com a melhora dos métodos de imagens ao eco...

  12. FUn: a framework for interactive visualizations of large, high-dimensional datasets on the web.

    Science.gov (United States)

    Probst, Daniel; Reymond, Jean-Louis

    2018-04-15

    During the past decade, big data have become a major tool in scientific endeavors. Although statistical methods and algorithms are well-suited for analyzing and summarizing enormous amounts of data, the results do not allow for a visual inspection of the entire data. Current scientific software, including R packages and Python libraries such as ggplot2, matplotlib and plot.ly, do not support interactive visualizations of datasets exceeding 100 000 data points on the web. Other solutions enable the web-based visualization of big data only through data reduction or statistical representations. However, recent hardware developments, especially advancements in graphical processing units, allow for the rendering of millions of data points on a wide range of consumer hardware such as laptops, tablets and mobile phones. Similar to the challenges and opportunities brought to virtually every scientific field by big data, both the visualization of and interaction with copious amounts of data are both demanding and hold great promise. Here we present FUn, a framework consisting of a client (Faerun) and server (Underdark) module, facilitating the creation of web-based, interactive 3D visualizations of large datasets, enabling record level visual inspection. We also introduce a reference implementation providing access to SureChEMBL, a database containing patent information on more than 17 million chemical compounds. The source code and the most recent builds of Faerun and Underdark, Lore.js and the data preprocessing toolchain used in the reference implementation, are available on the project website (http://doc.gdb.tools/fun/). daniel.probst@dcb.unibe.ch or jean-louis.reymond@dcb.unibe.ch.

  13. Soil science is way more fun than a proper job (Philippe Duchaufour Medal Lecture)

    Science.gov (United States)

    Smith, Pete

    2017-04-01

    Having now worked in soil science and climate change for over 20 years, I find myself giving one of the "old man / old woman" lectures at the EGU2017. You probably get picked to do this when your peers think that you are about to die soon, so I had better make the most of my time left! We are very fortunate to have a career in science, and to belong to the soils, and the wider, biogeosciences communities. If ever you get fed up with your teaching load, with your experiment that won't work, your model that you can't get running, or your paper that reviewers do not realise for the gem that you know it is, remember that we could be doing a 9 to 5 job, stuck in an office, with no opportunities to meet, talk and have fun with others from around the world with whom we share the same passion. I hope you enjoy your research careers and the time you spend with your work friends as much as I have. In this presentation I will reflect on how much I have learned about soils, climate, and the politics of how things get done over the past 20 years, and I will pick out some changes in our understanding of soils, and their role in the world as I go. I will draw on examples not only from my own work, but those of others, and will reflect on the some of the fun I have had while doing this "job".

  14. Nuclear networking.

    Science.gov (United States)

    Xie, Wei; Burke, Brian

    2017-07-04

    Nuclear lamins are intermediate filament proteins that represent important structural components of metazoan nuclear envelopes (NEs). By combining proteomics and superresolution microscopy, we recently reported that both A- and B-type nuclear lamins form spatially distinct filament networks at the nuclear periphery of mouse fibroblasts. In particular, A-type lamins exhibit differential association with nuclear pore complexes (NPCs). Our studies reveal that the nuclear lamina network in mammalian somatic cells is less ordered and more complex than that of amphibian oocytes, the only other system in which the lamina has been visualized at high resolution. In addition, the NPC component Tpr likely links NPCs to the A-type lamin network, an association that appears to be regulated by C-terminal modification of various A-type lamin isoforms. Many questions remain, however, concerning the structure and assembly of lamin filaments, as well as with their mode of association with other nuclear components such as peripheral chromatin.

  15. Folding and unfolding phylogenetic trees and networks.

    Science.gov (United States)

    Huber, Katharina T; Moulton, Vincent; Steel, Mike; Wu, Taoyang

    2016-12-01

    Phylogenetic networks are rooted, labelled directed acyclic graphswhich are commonly used to represent reticulate evolution. There is a close relationship between phylogenetic networks and multi-labelled trees (MUL-trees). Indeed, any phylogenetic network N can be "unfolded" to obtain a MUL-tree U(N) and, conversely, a MUL-tree T can in certain circumstances be "folded" to obtain aphylogenetic network F(T) that exhibits T. In this paper, we study properties of the operations U and F in more detail. In particular, we introduce the class of stable networks, phylogenetic networks N for which F(U(N)) is isomorphic to N, characterise such networks, and show that they are related to the well-known class of tree-sibling networks. We also explore how the concept of displaying a tree in a network N can be related to displaying the tree in the MUL-tree U(N). To do this, we develop aphylogenetic analogue of graph fibrations. This allows us to view U(N) as the analogue of the universal cover of a digraph, and to establish a close connection between displaying trees in U(N) and reconciling phylogenetic trees with networks.

  16. Cognitive-Behavioural Analysis System of Psychotherapy (CBASP), a drug, or their combination: differential therapeutics for persistent depressive disorder: a study protocol of an individual participant data network meta-analysis

    Science.gov (United States)

    Schramm, Elisabeth; Weitz, Erica S; Salanti, Georgia; Efthimiou, Orestis; Michalak, Johannes; Watanabe, Norio; Keller, Martin B; Kocsis, James H; Klein, Daniel N; Cuijpers, Pim

    2016-01-01

    Introduction Despite important advances in psychological and pharmacological treatments of persistent depressive disorders in the past decades, their responses remain typically slow and poor, and differential responses among different modalities of treatments or their combinations are not well understood. Cognitive-Behavioural Analysis System of Psychotherapy (CBASP) is the only psychotherapy that has been specifically designed for chronic depression and has been examined in an increasing number of trials against medications, alone or in combination. When several treatment alternatives are available for a certain condition, network meta-analysis (NMA) provides a powerful tool to examine their relative efficacy by combining all direct and indirect comparisons. Individual participant data (IPD) meta-analysis enables exploration of impacts of individual characteristics that lead to a differentiated approach matching treatments to specific subgroups of patients. Methods and analysis We will search for all randomised controlled trials that compared CBASP, pharmacotherapy or their combination, in the treatment of patients with persistent depressive disorder, in Cochrane CENTRAL, PUBMED, SCOPUS and PsycINFO, supplemented by personal contacts. Individual participant data will be sought from the principal investigators of all the identified trials. Our primary outcomes are depression severity as measured on a continuous observer-rated scale for depression, and dropouts for any reason as a proxy measure of overall treatment acceptability. We will conduct a one-step IPD-NMA to compare CBASP, medications and their combinations, and also carry out a meta-regression to identify their prognostic factors and effect moderators. The model will be fitted in OpenBUGS, using vague priors for all location parameters. For the heterogeneity we will use a half-normal prior on the SD. Ethics and dissemination This study requires no ethical approval. We will publish the findings in a peer

  17. NETWORK CODING BY BEAM FORMING

    DEFF Research Database (Denmark)

    2013-01-01

    Network coding by beam forming in networks, for example, in single frequency networks, can provide aid in increasing spectral efficiency. When network coding by beam forming and user cooperation are combined, spectral efficiency gains may be achieved. According to certain embodiments, a method...... cooperating with the plurality of user equipment to decode the received data....

  18. An Efficient Approach for Lipase-Catalyzed Synthesis of Retinyl Laurate Nutraceutical by Combining Ultrasound Assistance and Artificial Neural Network Optimization

    Directory of Open Access Journals (Sweden)

    Shang-Ming Huang

    2017-11-01

    Full Text Available Although retinol is an important nutrient, retinol is highly sensitive to oxidation. At present, some ester forms of retinol are generally used in nutritional supplements because of its stability and bioavailability. However, such esters are commonly synthesized by chemical procedures which are harmful to the environment. Thus, this study utilized a green method using lipase as a catalyst with sonication assistance to produce a retinol derivative named retinyl laurate. Moreover, the process was optimized by an artificial neural network (ANN. First, a three-level-four-factor central composite design (CCD was employed to design 27 experiments, which the highest relative conversion was 82.64%. Further, the optimal architecture of the CCD-employing ANN was developed, including the learning Levenberg-Marquardt algorithm, the transfer function (hyperbolic tangent, iterations (10,000, and the nodes of the hidden layer (6. The best performance of the ANN was evaluated by the root mean squared error (RMSE and the coefficient of determination (R2 from predicting and observed data, which displayed a good data-fitting property. Finally, the process performed with optimal parameters actually obtained a relative conversion of 88.31% without long-term reactions, and the lipase showed great reusability for biosynthesis. Thus, this study utilizes green technology to efficiently produce retinyl laurate, and the bioprocess is well established by ANN-mediated modeling and optimization.

  19. An Efficient Approach for Lipase-Catalyzed Synthesis of Retinyl Laurate Nutraceutical by Combining Ultrasound Assistance and Artificial Neural Network Optimization.

    Science.gov (United States)

    Huang, Shang-Ming; Li, Hsin-Ju; Liu, Yung-Chuan; Kuo, Chia-Hung; Shieh, Chwen-Jen

    2017-11-15

    Although retinol is an important nutrient, retinol is highly sensitive to oxidation. At present, some ester forms of retinol are generally used in nutritional supplements because of its stability and bioavailability. However, such esters are commonly synthesized by chemical procedures which are harmful to the environment. Thus, this study utilized a green method using lipase as a catalyst with sonication assistance to produce a retinol derivative named retinyl laurate. Moreover, the process was optimized by an artificial neural network (ANN). First, a three-level-four-factor central composite design (CCD) was employed to design 27 experiments, which the highest relative conversion was 82.64%. Further, the optimal architecture of the CCD-employing ANN was developed, including the learning Levenberg-Marquardt algorithm, the transfer function (hyperbolic tangent), iterations (10,000), and the nodes of the hidden layer (6). The best performance of the ANN was evaluated by the root mean squared error (RMSE) and the coefficient of determination ( R ²) from predicting and observed data, which displayed a good data-fitting property. Finally, the process performed with optimal parameters actually obtained a relative conversion of 88.31% without long-term reactions, and the lipase showed great reusability for biosynthesis. Thus, this study utilizes green technology to efficiently produce retinyl laurate, and the bioprocess is well established by ANN-mediated modeling and optimization.

  20. Combination of artificial neural network and genetic algorithm method for modeling of methylene blue adsorption onto wood sawdust from water samples.

    Science.gov (United States)

    Khajeh, Mostafa; Sarafraz-Yazdi, Ali; Natavan, Zahra Bameri

    2016-03-01

    The aim of this research was to develop a low price and environmentally friendly adsorbent with abundant of source to remove methylene blue (MB) from water samples. Sawdust solid-phase extraction coupled with high-performance liquid chromatography was used for the extraction and determination of MB. In this study, an experimental data-based artificial neural network model is constructed to describe the performance of sawdust solid-phase extraction method for various operating conditions. The pH, time, amount of sawdust, and temperature were the input variables, while the percentage of extraction of MB was the output. The optimum operating condition was then determined by genetic algorithm method. The optimized conditions were obtained as follows: 11.5, 22.0 min, 0.3 g, and 26.0°C for pH of the solution, extraction time, amount of adsorbent, and temperature, respectively. Under these optimum conditions, the detection limit and relative standard deviation were 0.067 μg L(-1) and <2.4%, respectively. The Langmuir and Freundlich adsorption models were applied to describe the isotherm constant and for the removal and determination of MB from water samples. © The Author(s) 2013.

  1. A Combination of Stable Isotope Probing, Illumina Sequencing, and Co-occurrence Network to Investigate Thermophilic Acetate- and Lactate-Utilizing Bacteria.

    Science.gov (United States)

    Sun, Weimin; Krumins, Valdis; Dong, Yiran; Gao, Pin; Ma, Chunyan; Hu, Min; Li, Baoqin; Xia, Bingqing; He, Zijun; Xiong, Shangling

    2018-01-01

    Anaerobic digestion is a complicated microbiological process that involves a wide diversity of microorganisms. Acetate is one of the most important intermediates, and interactions between acetate-oxidizing bacteria and archaea could play an important role in the formation of methane in anoxic environments. Anaerobic digestion at thermophilic temperatures is known to increase methane production, but the effects on the microbial community are largely unknown. In the current study, stable isotope probing was used to characterize acetate- and lactate-oxidizing bacteria in thermophilic anaerobic digestion. In microcosms fed 13 C-acetate, bacteria related to members of Clostridium, Hydrogenophaga, Fervidobacterium, Spirochaeta, Limnohabitans, and Rhodococcus demonstrated elevated abundances of 13 C-DNA fractions, suggesting their activities in acetate oxidation. In the treatments fed 13 C-lactate, Anaeromyxobacter, Desulfobulbus, Syntrophus, Cystobacterineae, and Azospira were found to be the potential thermophilic lactate utilizers. PICRUSt predicted that enzymes related to nitrate and nitrite reduction would be enriched in 13 C-DNA fractions, suggesting that the acetate and lactate oxidation may be coupled with nitrate and/or nitrite reduction. Co-occurrence network analysis indicated bacterial taxa not enriched in 13 C-DNA fractions that may also play a critical role in thermophilic anaerobic digestion.

  2. Exploring the potential relationship between indoor air quality and the concentration of airborne culturable fungi: a combined experimental and neural network modeling study.

    Science.gov (United States)

    Liu, Zhijian; Cheng, Kewei; Li, Hao; Cao, Guoqing; Wu, Di; Shi, Yunjie

    2018-02-01

    Indoor airborne culturable fungi exposure has been closely linked to occupants' health. However, conventional measurement of indoor airborne fungal concentration is complicated and usually requires around one week for fungi incubation in laboratory. To provide an ultra-fast solution, here, for the first time, a knowledge-based machine learning model is developed with the inputs of indoor air quality data for estimating the concentration of indoor airborne culturable fungi. To construct a database for statistical analysis and model training, 249 data groups of air quality indicators (concentration of indoor airborne culturable fungi, indoor/outdoor PM 2.5 and PM 10 concentrations, indoor temperature, indoor relative humidity, and indoor CO 2 concentration) were measured from 85 residential buildings of Baoding (China) during the period of 2016.11.15-2017.03.15. Our results show that artificial neural network (ANN) with one hidden layer has good prediction performances, compared to a support vector machine (SVM). With the tolerance of ± 30%, the prediction accuracy of the ANN model with ten hidden nodes can at highest reach 83.33% in the testing set. Most importantly, we here provide a quick method for estimating the concentration of indoor airborne fungi that can be applied to real-time evaluation.

  3. Tip Deflection Determination of a Barrel for the Effect of an Accelerating Projectile Before Firing Using Finite Element and Artificial Neural Network Combined Algorithm

    Directory of Open Access Journals (Sweden)

    Mehmet Akif Koç

    Full Text Available Abstract For realistic applications, design and control engineers have limited modelling options in dealing with some vibration problems that hold many nonlinearity such as non-uniform geometry, variable velocity loadings, indefinite damping cases, etc. For these reasons numerous time consuming experimental studies at high costs must be done for determining the actual behaviour such nonlinear systems. However, using advantages of multiple computational methods like Finite Element Method (FEM together with an Artificial Intelligence (ANN, many complicated engineering problems can be handled and solved to some extent. This study, proposes a new collective method to deal with the nonlinear vibrations of the barrels in order to fulfil accurate shooting expectancy. Using known analytical methods, in practical, to determine dynamic behaviour of the barrel beam is not possible for all conditions of firing that include numerous varieties of ammunition for different purposes, and each projectile of different ammunition has different mass and exit velocity. In order to cover all cases this study proposes a new method that combines a precise FEM with ANN, and can be used for determining the exact dynamic behaviour of a barrel for some cases and then for precisely predicting the behaviour for all other possible cases of firing. In this study, the whole nonlinear behaviour of an antiaircraft barrel were obtained with 3.5% accuracy errors by ANN trained by FEM using calculated analysis results of ammunitions for a particular range. The proposed FEM-ANN combined method can be very useful for design and control engineers in design and control of barrels in order to compensate the effect of nonlinear vibrations of a barrel for achieving a higher shooting accuracy; and can reduce high-cost experimental works.

  4. Systematic review and network meta-analysis of combination and monotherapy treatments in disease-modifying antirheumatic drug-experienced patients with rheumatoid arthritis: analysis of American College of Rheumatology criteria scores 20, 50, and 70

    Science.gov (United States)

    Orme, Michelle E; MacGilchrist, Katherine S; Mitchell, Stephen; Spurden, Dean; Bird, Alex

    2012-01-01

    Background Biologic disease-modifying antirheumatic drugs (bDMARDs) extend the treatment choices for rheumatoid arthritis patients with suboptimal response or intolerance to conventional DMARDs. The objective of this systematic review and meta-analysis was to compare the relative efficacy of EU-licensed bDMARD combination therapy or monotherapy for patients intolerant of or contraindicated to continued methotrexate. Methods Comprehensive, structured literature searches were conducted in Medline, Embase, and the Cochrane Library, as well as hand-searching of conference proceedings and reference lists. Phase II or III randomized controlled trials reporting American College of Rheumatology (ACR) criteria scores of 20, 50, and 70 between 12 and 30 weeks’ follow-up and enrolling adult patients meeting ACR classification criteria for rheumatoid arthritis previously treated with and with an inadequate response to conventional DMARDs were eligible. To estimate the relative efficacy of treatments whilst preserving the randomized comparisons within each trial, a Bayesian network meta-analysis was conducted in WinBUGS using fixed and random-effects, logit-link models fitted to the binomial ACR 20/50/70 trial data. Results The systematic review identified 10,625 citations, and after a review of 2450 full-text papers, there were 29 and 14 eligible studies for the combination and monotherapy meta-analyses, respectively. In the combination analysis, all licensed bDMARD combinations had significantly higher odds of ACR 20/50/70 compared to DMARDs alone, except for the rituximab comparison, which did not reach significance for the ACR 70 outcome (based on the 95% credible interval). The etanercept combination was significantly better than the tumor necrosis factor-α inhibitors adalimumab and infliximab in improving ACR 20/50/70 outcomes, with no significant differences between the etanercept combination and certolizumab pegol or tocilizumab. Licensed-dose etanercept, adalimumab

  5. Knowledge management in international networks

    NARCIS (Netherlands)

    Man, de A.P.

    2006-01-01

    Networks and knowledge are intimately connected. Networks are believed to be innovative because of the smooth transfer, combination and creation of knowledge that can take place in them. Interestingly however, knowledge management research has hardly studied knowledge management techniques in

  6. Effective professional networking.

    Science.gov (United States)

    Goolsby, Mary Jo; Knestrick, Joyce M

    2017-08-01

    The reasons for nurse practitioners to develop a professional network are boundless and are likely to change over time. Networking opens doors and creates relationships that support new opportunities, personal development, collaborative research, policy activism, evidence-based practice, and more. Successful professional networking involves shared, mutually beneficial interactions between individuals and/or individuals and groups, regardless of whether it occurs face to face or electronically. This article combines nuggets from the literature with guidance based on the authors' combined experience in networking activities at the local, national, and international levels. ©2017 American Association of Nurse Practitioners.

  7. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  8. 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

  9. Modified Aggressive Packet Combining Scheme

    International Nuclear Information System (INIS)

    Bhunia, C.T.

    2010-06-01

    In this letter, a few schemes are presented to improve the performance of aggressive packet combining scheme (APC). To combat error in computer/data communication networks, ARQ (Automatic Repeat Request) techniques are used. Several modifications to improve the performance of ARQ are suggested by recent research and are found in literature. The important modifications are majority packet combining scheme (MjPC proposed by Wicker), packet combining scheme (PC proposed by Chakraborty), modified packet combining scheme (MPC proposed by Bhunia), and packet reversed packet combining (PRPC proposed by Bhunia) scheme. These modifications are appropriate for improving throughput of conventional ARQ protocols. Leung proposed an idea of APC for error control in wireless networks with the basic objective of error control in uplink wireless data network. We suggest a few modifications of APC to improve its performance in terms of higher throughput, lower delay and higher error correction capability. (author)

  10. Metagovernance, network structure, and legitimacy

    DEFF Research Database (Denmark)

    Daugbjerg, Carsten; Fawcett, Paul

    2017-01-01

    This article develops a heuristic for comparative governance analysis. The heuristic depicts four network types by combining network structure with the state’s capacity to metagovern. It suggests that each network type produces a particular combination of input and output legitimacy. We illustrate...... the heuristic and its utility using a comparative study of agri-food networks (organic farming and land use) in four countries, which each exhibit different combinations of input and output legitimacy respectively. The article concludes by using a fifth case study to illustrate what a network type that produces...... high levels of input and output legitimacy might look like....

  11. Integração de três conceitos: função executiva, memória de trabalho e aprendizado

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Mourão Junior

    Full Text Available O presente artigo discute o conceito de função executiva enquanto um processo de integração temporal, envolvendo funções como o ajuste preparatório, o controle inibitório e a memória de trabalho. Em seguida questiona o modelo multicomponente de Baddeley para a memória de trabalho e propõe uma nova classificação da função executiva que engloba os modelos de Fuster e de Baddeley. Finalmente revisita o conceito neurobiológico de aprendizado e sugere uma abordagem para se avaliar os déficits de aprendizagem que leve em conta a função executiva como a pedra angular do processo cognitivo.

  12. Marketingová strategie lyžařské školy School 4 fun.

    OpenAIRE

    Burešová, Eva

    2011-01-01

    The aim of diploma thesis is to suggest new marketing strategy of ski and snowboard school SCHOOL 4 FUN for this year 2011/2012 including proposals and recommendation for its improvement. Suggested marketing strategy is the solution for suitable position of limited financial means for the company to maintain competitive advantage, increase its sale, thus increase its revenue at the same time. To achieve given aim, the technique of competitive analysis, marketing mix and SWOT analysis was used...

  13. Observação do desenvolvimento de linguagem e funções auditiva e visual em lactentes

    Directory of Open Access Journals (Sweden)

    Lima Maria Cecília Marconi Pinheiro

    2004-01-01

    Full Text Available OBJETIVO: Investigar o desenvolvimento da linguagem e das funções auditiva e visual em lactentes de creche, a partir da avaliação realizada por educadores. MÉTODOS: Foram avaliados 115 lactentes, nos anos de 1998 a 2001, usuários de uma creche da área da saúde de uma universidade do Estado de São Paulo. Foi utilizado o "Protocolo da Observação do Desenvolvimento de Linguagem e das Funções Auditiva e Visual", com 39 provas no total, para a avaliação dos lactentes de 3 até 12 meses de idade. A aplicação desse Protocolo foi feita pelas educadoras da creche, devidamente treinadas. Utilizou-se o teste de Qui-quadrado ou Exato de Fisher. O nível de significância adotado foi de 5%. RESULTADOS: Os lactentes apresentaram um padrão diferente no desenvolvimento da linguagem quanto ao início do balbucio e das primeiras palavras, bem como na função visual, quanto à imitação e uso de jogos gestuais e de seguir ordem com uso de gestos. CONCLUSÕES: O ambiente creche propicia condições para um outro padrão de desenvolvimento de linguagem e das funções auditiva e visual. Ações de prevenção na creche devem integrar as áreas de saúde e educação num objetivo comum.

  14. When the going gets tough...: Self-motivation is associated with invigoration and fun.

    Science.gov (United States)

    Kazén, Miguel; Kuhl, Julius; Leicht, Eva-Maria

    2015-11-01

    Personality systems interaction (PSI) theory postulates two executive control modes in volitional action: Self-control and self-regulation (self-motivation). Self-control should deplete energy whereas self-motivation should maintain energy and result in invigoration. There were three groups of participants: Self-control, self-motivation, and pretend, who performed a resource-demanding Stroop-Shift and an anagram task. Performance and energy expenditure were examined in each task. Compared to the other groups, the self-motivation group showed increments in blood glucose throughout the experiment, indicating invigoration, and had better performance on the difficult Stroop-Shift task than the self-control group. Additionally, for the self-motivation group anagram performance correlated with less effort and ease of concentration and was moderated by fun in the task. These results are consonant with the predictions of PSI and self-determination theories. It is concluded that self-control depletes resources whereas self-motivation is associated with invigoration in carrying resource-demanding tasks.

  15. Choose Health: Food, Fun, and Fitness Youth Curriculum Promotes Positive Behaviors.

    Science.gov (United States)

    Wolfe, Wendy S; Scott-Pierce, Michelle; Dollahite, Jamie

    2017-11-20

    Evaluate whether participation in Choose Health: Food, Fun, and Fitness (CHFFF), a hands-on, experiential curriculum aimed at third- to sixth-graders, resulted in improvements in the targeted obesity and chronic disease prevention behaviors. The researchers evaluated CHFFF in low-income youth participating in 2 federal programs in New York State during 2013-2015. Food and activity behaviors were assessed using the Expanded Food and Nutrition Education Program third- through fifth- and sixth- through eighth-grade pre-post surveys, along with 2 sets of added CHFFF-specific items completed by subsamples. Educators trained in CHFFF had youth complete the surveys as they delivered the curriculum, primarily in schools and after-school programs. Paired t tests showed significant (P < .01) positive changes before to after CHFFF education for consumption of vegetables, fruits, sweetened drinks, nutrition label reading, and other food and activity behaviors. Results provide practice-based evidence that CHFFF promotes positive behavior change in participating youth. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

  16. Fuel not fun: Reinterpreting attenuated brain responses to reward in obesity.

    Science.gov (United States)

    Kroemer, Nils B; Small, Dana M

    2016-08-01

    There is a well-established literature linking obesity to altered dopamine signaling and brain response to food-related stimuli. Neuroimaging studies frequently report enhanced responses in dopaminergic regions during food anticipation and decreased responses during reward receipt. This has been interpreted as reflecting anticipatory "reward surfeit", and consummatory "reward deficiency". In particular, attenuated response in the dorsal striatum to primary food rewards is proposed to reflect anhedonia, which leads to overeating in an attempt to compensate for the reward deficit. In this paper, we propose an alternative view. We consider brain response to food-related stimuli in a reinforcement-learning framework, which can be employed to separate the contributions of reward sensitivity and reward-related learning that are typically entangled in the brain response to reward. Consequently, we posit that decreased striatal responses to milkshake receipt reflect reduced reward-related learning rather than reward deficiency or anhedonia because reduced reward sensitivity would translate uniformly into reduced anticipatory and consummatory responses to reward. By re-conceptualizing reward deficiency as a shift in learning about subjective value of rewards, we attempt to reconcile neuroimaging findings with the putative role of dopamine in effort, energy expenditure and exploration and suggest that attenuated brain responses to energy dense foods reflect the "fuel", not the fun entailed by the reward. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Putting program evaluation into practice: enhancing the Girls Just Wanna Have Fun program.

    Science.gov (United States)

    Bean, Corliss N; Kendellen, Kelsey; Halsall, Tanya; Forneris, Tanya

    2015-04-01

    In recent years there has been a call for increased community physical activity and sport programs for female youth that are deliberately structured to foster positive developmental outcomes. In addition, researchers have recognized the need to empirically evaluate such programs to ensure that youth are provided with optimal opportunities to thrive. This study represents a utilization-focused evaluation of Girls Just Wanna Have Fun, a female-only physical activity-based life skills community program. A utilization-focused evaluation is particularly important when the evaluation is to help stakeholders utilize the findings in practice. The purpose of this study was twofold: (a) to gain an understanding of the ongoing successes and challenges after year two of program implementation and (b) to examine how the adaptations made based on feedback from the first year evaluation were perceived as impacting the program. From interviews with youth participants and program leaders, three main themes with eight sub-themes emerged. The main themes were: (a) applying lessons learned can make a significant difference, (b) continually implementing successful strategies, and (c) ongoing challenges. Overall, this evaluation represents an important step in understanding how to improve program delivery to better meet the needs of the participants in community-based programming. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Estresse e função reprodutiva feminina Stress and female reproductive function

    Directory of Open Access Journals (Sweden)

    Simone da Nóbrega Tomaz Moreira

    2005-03-01

    Full Text Available Este artigo discute a relação do estresse sobre a função reprodutiva, considerando que a infertilidade pode ter causas psicológicas (hipótese da psicogênese ou pode ser a origem do estresse psicológico. A presença do estresse tem o potencial de ativar o eixo hipotálamo-hipófise-adrenal, o qual, inibe o eixo hipotálamo-hipófise-ovariano, levando à paralisação temporária das menstruações. Esse processo pode resultar em infertilidade transitória para as mulheres. Os autores enfatizam a necessidade de uma abordagem psicológica nos serviços de reprodução, objetivando trabalhar as tensões e frustrações advindas da infertilidade e do seu tratamento.This article discusses the relationship between stress and reproduction considering that infertility could bear psychological causes (psychogenesis hypothesis or could be caused by psychological stress. Stress has the potential of activating the hypothalamus-hypophisis-adrenal axis inhibiting the hypothalamus-hypophisis-ovarian axis leading to temporary menstruation paralysis. This process could result in a transitory infertility of women. The authors emphasize the need of a psychological approach in reproduction services with the objective of treating tensions and frustrations derived from infertility and its treatment.

  19. Social support from teachers mediates physical activity behavior change in children participating in the Fit-4-Fun intervention.

    Science.gov (United States)

    Eather, Narelle; Morgan, Philip J; Lubans, David R

    2013-05-28

    Few studies have examined the mediators of behavior change in successful school-based physical activity interventions. The aim of this study was to explore potential mediators of physical activity in the Fit-4-Fun program for primary school children. Group randomized controlled trial. Four primary schools were recruited in April, 2011 and randomized by school into intervention or control conditions. Participants included 213 children (mean age = 10.7 years ± 0.6; 52.2% female) with the treatment group (n = 118) completing the 8-week multi-component Fit-4-Fun program. Participants were assessed at baseline, 3- and 6-months. Physical activity was measured using Yamax SW700 pedometers (mean steps/day) and questionnaires were used to assess constructs from Social Cognitive Theory and Competence Motivation Theory. Hypothesized mediators measured included social support from peers, parents and teachers; physical activity self-efficacy (barrier and task); enjoyment; and perceived school physical environment. Mediation was assessed using Preacher and Hayes' multiple mediation regression SPSS macro. Action theory (A), conceptual theory (B) and the significance of the product of coefficients (AB) are reported. The intervention had a significant effect on physical activity (pFun program successfully targeted social support for physical activity provided by classroom teachers which contributed to improved physical activity in children. These results demonstrate that classroom teachers play a key role in influencing physical activity behavior outcomes in children.Trial Registration No: ACTRN12611000976987.

  20. Fun Seeking and Reward Responsiveness Moderate the Effect of the Behavioural Inhibition System on Coping-Motivated Problem Gambling.

    Science.gov (United States)

    Keough, Matthew T; Wardell, Jeffrey D; Hendershot, Christian S; Bagby, R Michael; Quilty, Lena C

    2017-09-01

    Gray's Reinforcement Sensitivity Theory (RST) predicts that the Behavioral Inhibition System (BIS) may relate to coping-motivated problem gambling, given its central role in anxiety. Studies examining the BIS-problem gambling association, however, are mixed. The revised RST posits that the Behavioral Approach System (BAS) may moderate the effect of the BIS on coping-motivated problem gambling. A concurrently strong BAS may highlight the negatively reinforcing effects of gambling, which may strengthen coping motives and increase gambling-related harms. We examined these interactive effects to clarify the moderators and mediators of the negative reinforcement pathway to problem gambling. Data came from a larger investigation of problem gambling among individuals with mood disorders. All participants (N = 275) met criteria for a lifetime depressive or bipolar disorder. During a two-day assessment, participants completed a diagnostic assessment and self-reports. Mediated moderation path analysis showed positive indirect effects from the BIS to problem gambling via coping motives at high, but not at low, levels of BAS-Reward Responsiveness and BAS-Fun Seeking. Enhancement motives were also found to mediate the associations of BAS-Fun Seeking and BAS-Drive with problem gambling. Reward Responsiveness and Fun Seeking facets of the BAS may strengthen coping gambling motives within the mood disorders.