5,998 research outputs found

    Large-amplitude electron-acoustic solitons in a dusty plasma with kappa-distributed electrons

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    The Sagdeev pseudopotential method is used to investigate the occurrence and the dynamics of fully nonlinear electrostatic solitary structures in a plasma containing suprathermal hot electrons, in the presence of massive charged dust particles in the background. The soliton existence domain is delineated, and its parametric dependence on different physical parameters is clarified.Comment: 3 pages, 1 figure, presented as a poster at the 6th International Conference on the Physics of Dusty Plasmas (ICPDP6), Garmisch-Partenkirchen, Germany, 201

    ACCESS POINT NAME (APN)/DATA NETWORK NAME (DNN) BASED AUTO-ANCHORING OF FIFTH GENERATION/NEXT GENERATION TRAFFIC IN WI-FI

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    Private Third Generation Partnership Project (3GPP) Fifth Generation/next Generation (5G/nG) network environments will have a mix of access technologies, such as Wi-Fi6 and 5G/nG Radio Access Network (RAN) technologies. Techniques presented herein provide for the capability to transport and intelligently anchor 5G/nG data using a Wi-Fi system, which may allow for private 5G/nG onboarding utilizing the Wi-Fi system

    Induction of Mutation in Rough Lemon (Citrus jambhiri Lush.) Using Gamma Rays

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    The present investigation was carried out to study variability induced by gamma rays with respect to vegetative characters and LD50 dose in Rough lemon. Rough lemon seeds were gamma irradiated at doses of 0, 4, 6 and 8 kr along with control. Seed germination decreased with increasing dose of gamma radiation. Seedling height and leaf size also decreased with increasing dose of gamma radiation, whereas, apical branching, number of branches/seedling, number of variegated / albino seedlings and number of leaves increased with increasing dose of gamma radiation. Maximum variability for seedling height, number of leaves, leaf size, colour, internode length, and per cent apical branching was observed at two months from sowing in seeds treated with 8 kr dose of gamma radiation. Variability for all characters was, however, found to be minimum in the control

    Regional gene repression by DNA double-strand breaks in G1 phase cells

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    DNA damage responses (DDR) to double-strand breaks (DSBs) alter cellular transcription programs at the genome-wide level. Through processes that are less well understood, DSBs also alter transcriptional responses locally, which may be important for efficient DSB repair. Here, we developed an approach to elucidate th

    PROACTIVE EXCHANGE OF DATA BETWEEN CLOUD PROVIDERS VIA CONTROLLER COORDINATION AND TRIGGER DYNAMIC WORKFLOWS

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    A multi-cloud Software Defined Network (SDN) controller proactively learns insights about subscribers, such as enterprise users, end users, and/or other cloud providers. Based on the learned insights, the multi-SDN controller applies dynamic policies on other cloud provides to which those subscribers are attached to. The multi-cloud SDN controller co-ordinates with various cloud providers, enterprise network controllers, and Internet Service Providers (ISPs) to proactively notify other cloud providers with information about affected users so that those providers can install additional resources at cloud edge/core on the fly. Additionally, the multi-cloud SDN controller facilitates a warm hand off from one cloud region to another cloud region. When the multi-cloud SDN controller learns about an enterprise outage, it proactively notifies other cloud providers of the outage event and the other cloud providers can use this for a warm hand off of session to the region(s) through which the users will be reconnected. The likely regions are derived based on telemetry obtained from multi-cloud SDN controller. The multi-cloud SDN controller also triggers a proactive cleanup of user context of the cloud provider side. The cloud provider cleans up after the connection reset event based on information from the multi-cloud SDN controller, rather than wait on a timeout of the connection

    Evaluation of a flipped examination model implemented in a final-year undergraduate pharmacotherapeutics course

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    Ā© 2019, American Association of Colleges of Pharmacy. All rights reserved. Objective. To assess final-year pharmacy studentsā€™ performance on and evaluate their experience with a ā€œflipped examinationā€ vs a traditional examination for an advanced clinical pharmacy course. Methods. Students devised multiple-choice questions for the flipped examination. The Biggs revised 2-factor Study Process Questionnaire was administered before and after the examination to assess any possible changes in the studentsā€™ perceptions of their level of engagement in the learning process. Focus group discussions also were conducted to further gauge the studentsā€™ feedback and insights into the flipped examination experience. Results. Changes in mean total study process scores at the deep and surface levels of learning were significant. The flipped examination experience was enjoyable, facilitated a less-stressful learning environment, and improved the studentsā€™ learning satisfaction, knowledge, and assessment grades. Conclusion. The flipped examination model is an innovative instructional approach that can bring about significant educational gains if designed well pedagogically

    Exploiting Machine Learning to Subvert Your Spam Filter

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    Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical machine learning, as used in the SpamBayes spam filter, to render it uselessā€”even if the adversaryā€™s access is limited to only 1 % of the training messages. We further demonstrate a new class of focused attacks that successfully prevent victims from receiving specific email messages. Finally, we introduce two new types of defenses against these attacks.

    Statefinder -- a new geometrical diagnostic of dark energy

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    We introduce a new cosmological diagnostic pair {r,s}\lbrace r,s\rbrace called Statefinder. The Statefinder is dimensionless and, like the Hubble and deceleration parameters H(z)H(z) and q(z)q(z), is constructed from the scale factor of the Universe and its derivatives only. The parameter r(z)r(z) forms the next step in the hierarchy of geometrical cosmological parameters used to study the Universe after HH and qq, while the parameter s(z)s(z) is a linear combination of qq and rr chosen in such a way that it does not depend upon the dark energy density Ī©X(z)\Omega_X(z). The Statefinder pair {r,s}\lbrace r,s\rbrace is algebraically related to the the dark energy pressure-to-energy ratio w=p/Ļµw=p/\epsilon and its time derivative, and sheds light on the nature of dark energy/quintessence. Its properties allow to usefully differentiate between different forms of dark energy with constant and variable ww, including a cosmological constant (w=āˆ’1w = -1). The Statefinder pair can be determined to very good accuracy from a SNAP type experiment.Comment: 7 pages, 3 figures. Final version to be published in JETP Lett., presentation shortened, references added and updated, consideration of brane cosmological models included, conclusions unchange

    DYNAMIC TELEMETRY PROFILE ENFORCEMENT IN A CONTROLLER NETWORK

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    Because telemetry processing can involve high resource usage, such processing is typically provided via a cloud infrastructure. However, there are drawbacks to current implementations involving such cloud infrastructure processing. For example, such processing typically follows standard processing patterns. Yet, with the increasing complexity of different network use cases, there are scenarios that would benefit from dynamic telemetry processing. Presented herein are techniques through which multiple device telemetry profiles can allow a cloud controller to dynamically match a telemetry profile to specific conditions for a tenant network. Each telemetry profile may include selections for data processing through priority and secured queues. Additionally, the cloud controller may have reverse telemetry policies to push reverse telemetry to the customer edge when original usage telemetry data is retrieved, processed, and/or transferred
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