88 research outputs found
Author response
No full textDetecting pathogens and mounting immune responses upon infection is crucial for animal health. However, these responses come at a high metabolic price (McKean and Lazzaro, 2011, Kominsky et al., 2010), and avoiding pathogens before infection may be advantageous. The bacterial endotoxins lipopolysaccharides (LPS) are important immune system infection cues (Abbas et al., 2014), but it remains unknown whether animals possess sensory mechanisms to detect them prior to infection. Here we show that Drosophila melanogaster display strong aversive responses to LPS and that gustatory neurons expressing Gr66a bitter receptors mediate avoidance of LPS in feeding and egg laying assays. We found the expression of the chemosensory cation channel dTRPA1 in these cells to be necessary and sufficient for LPS avoidance. Furthermore, LPS stimulates Drosophila neurons in a TRPA1-dependent manner and activates exogenous dTRPA1 channels in human cells. Our findings demonstrate that flies detect bacterial endotoxins via a gustatory pathway through TRPA1 activation as conserved molecular mechanism.sponsorship: Vlaams Instituut voor Biotechnologie Alessia Soldano Luis Franco Guangda Liu Natalia Mora Emre Yaksi Bassem A Hassanr Fonds Wetenschappelijk Onderzoek G.0702.12 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0077.15 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0680.10 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0681.10 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0503.12 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0654.15 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0761.10N Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0596.12 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar Fonds Wetenschappelijk Onderzoek G.0565.07 Alessia Soldano Yeranddy A Alpizar Brett Boonen Alejandro Lopez-Requena Natalia Mora Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar KU Leuven GOA/14/011 Alessia Soldano Yeranddy A Alpizar Brett Boonen Luis Franco Alejandro Lopez-Requena Guangda Liu Natalia Mora Emre Yaksi Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar European Commission IUAP P7/13 Alessia Soldano Yeranddy A Alpizar Brett Boonen Luis Franco Alejandro Lopez-Requena Guangda Liu Natalia Mora Emre Yaksi Thomas Voets Rudi Vennekensr KU Leuven OT/12/091 Alessia Soldano Yeranddy A Alpizar Brett Boonen Luis Franco Alejandro Lopez-Requena Guangda Liu Natalia Mora Emre Yaksi Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talaverar KU Leuven PF-TRPLe Alessia Soldano Yeranddy A Alpizar Brett Boonen Luis Franco Alejandro Lopez-Requena Guangda Liu Natalia Mora Emre Yaksi Thomas Voets Rudi Vennekens Bassem A Hassan Karel Talavera (Vlaams Instituut voor Biotechnologie, Fonds Wetenschappelijk Onderzoek|G.0702.12, Fonds Wetenschappelijk Onderzoek|G.0077.15, Fonds Wetenschappelijk Onderzoek|G.0680.10, Fonds Wetenschappelijk Onderzoek|G.0681.10, Fonds Wetenschappelijk Onderzoek|G.0503.12, Fonds Wetenschappelijk Onderzoek|G.0654.15, Fonds Wetenschappelijk Onderzoek|G.0761.10N, Fonds Wetenschappelijk Onderzoek|G.0596.12, KU Leuven|GOA/14/011, KU Leuven|OT/12/091, European Commission|IUAP P7/13, KU Leuven PF-TRPLe)status: Publishe
Accurate prediction of international trade flows: Leveraging knowledge graphs and their embeddings
No full textKnowledge representation (KR) is vital in designing symbolic notations to represent real-world facts and facilitate automated decision-making tasks. Knowledge graphs (KGs) have emerged so far as a popular form of KR, offering a contextual and human-like representation of knowledge. In international economics, KGs have proven valuable in capturing complex interactions between commodities, companies, and countries. By putting the gravity model, which is a common economic framework, into the process of building KGs, important factors that affect trade relationships can be taken into account, making it possible to predict international trade patterns. This paper proposes an approach that leverages Knowledge Graph embeddings for modeling international trade, focusing on link prediction using embeddings. Thus, valuable insights are offered to policymakers, businesses, and economists, enabling them to anticipate the effects of changes in the international trade system. Moreover, the integration of traditional machine learning methods with KG embeddings, such as decision trees and graph neural networks are also explored. The research findings demonstrate the potential for improving prediction accuracy and provide insights into embedding explainability in knowledge representation. The paper also presents a comprehensive analysis of the influence of embedding methods on other intelligent algorithms
Les plages de Beyrouth : privatisation et communautarisation d’espaces publics
No full textBeirut beaches appeared on the western side of the city, which was once the most cosmopolitan district. The author describes these public spaces and the way of life prior to the war. He also considers the main evolutions that took place through the war period.El-Jisr Bassem. Les plages de Beyrouth : privatisation et communautarisation d’espaces publics. In: Reconstruire Beyrouth. Les paris sur le possible
Academic freedom at Palestinian universities : a human rights report
No full textBassem Eid traces the history of Palestinian Universities over three
periods - the Israeli occupation early 1970s until the Intifada, the
Intifada and its aftermath and the current era. The author examines
the serious problems and restrictions faced by University students
and intellectuals. He denounces a series of human rights violations
particularly the rights of freedom of expression and association. Such
violations include deportations, violence against students, arrests and
detentions without formal charges and unfair dismissal of professors
who spoke their minds. These human rights violations are not solely
a result of Israeli oppression but also a result of the interference of
the Palestinian Authority. The author probes into the University
Security Administration and the presence of undercover agents
within the universities, who monitor and report the activities of
individuals, are associated with the Islamic bloc or who criticise the
Palestinian Authority.peer-reviewe
Corrections to “D2D-V2X-SDN: Taxonomy and Architecture Towards 5G Mobile Communication”
No full textIn the above article [1], the following author bios must be updated as their posts and positions were upgraded, and the profile picture of Bassem F. Felemban was previously incorrect.Scopu
Enquête sur l'applicabilité de l'apprentissage en profondeur et de la chaîne de blocs pour l'Internet des objets défini par logiciel
No full text5G mobile network has seen phenomenal growth in providing IoT services and applications. IoT devices are often battery-powered to perform their operations autonomously and serve a variety of situations, such as smart cities, autonomous cars, smart manufacturing, etc., thereby needing efficient energy consumption to extend their lifespan. IoT networks should provide i) an on-demand resource allocation to support adaptive horizontal and vertical scaling of the network resources; ii) flexible infrastructure virtualization that exploits in-network programmability capabilities to operate inside an SDN-enabled virtualization platform; iii) a device-driven and human-driven intelligence to address the issues of energy efficiency and ultra-low latency requirements for future reliable and real-time IoT applications. Despite the promise, IoT networks face several challenging issues stemming from resource constraints and low-computation performance. Additionally, IoT systems encounter several security and privacy concerns to prevent unauthorized access to smart devices and secure trust-less interactions between devices themselves and service providers on the Internet.To address this plethora of challenges, this thesis presents an energy-efficiency IoT system, less computation-intensive, easy to implement, and amenable to online adaptation to the variations of the network condition. In the first contribution, we introduce a novel IoT network virtualization approach based on SDN/NFV to offer a high degree of automation in service chaining delivery for IoT devices. The second contribution introduces a Deep Reinforcement Learning energy-efficient task assignment and scheduling in SDN-based fog IoT Network. Furthermore, we present a computing model for reducing network latency and traffic overhead by centralizing the network control and orchestration in a single SDN controller layer. The last contribution introduces a deep learning approach that combines SDN and blockchain to achieve task scheduling and offloading, improve the response rate of IoT services to offer high levelsof performance, and strive to perform dynamic resource management.Le réseau mobile 5G a connu une croissance phénoménale dans la fourniture de services et d'applications IoT. Les appareils IoT sont souvent alimentés par batterie pour effectuer leurs opérations de manière autonome et servir à diverses situations, telles que les villes intelligentes, les voitures autonomes, la fabrication intelligente, etc. ont donc besoin d'une consommation d'énergie efficace pour prolonger leur durée de vie. Les réseaux IoT devraient fournir: i) une allocation de ressources à la demande pour prendre en charge une mise à l'échelle horizontale et verticale adaptative des ressources du réseau; ii) une virtualisation d'infrastructure flexible qui exploite les capacités de programmabilité en réseau pour fonctionner à l'intérieur d'une plate-forme de virtualisation compatible SDN; iii) une intelligence pilotée par les appareils et pilotée par l'homme pour répondre aux problèmes d'efficacité énergétique et aux exigences de latence ultra-faible pour les futures applications IoT fiables et en temps réel. Malgré la promesse, le réseau IoT est confronté à plusieurs problèmes complexes liés à ses contraintes de ressources et à ses faibles performances de calcul. De plus, les systèmes IoT rencontrent plusieurs problèmes de sécurité et de confidentialité pour empêcher l'accès non autorisé aux appareils intelligents et pour sécuriser les interactions sans confiance entre les appareils eux-mêmes et avec les fournisseurs de services sur Internet.Pour relever cette pléthore de défis, cette thèse présente un système IoT à haut rendement énergétique, moins gourmand en calculs, facile à mettre en œuvre et pouvant être adapté en ligne aux variations de l'état du réseau. Dans la première contribution, nous introduisons une nouvelle approche de virtualisation de réseau IoT basée sur SDN/NFV pour offrir un degré élevé d'automatisation dans la prestation de chaînage de services pour les appareils IoT. Dans la deuxième contribution, nous introduisons une attribution et une planification des tâches économes en énergie par Apprentissage par Renforcement dans un réseau IoT de brouillard basé sur SDN. Nous présentons un modèle informatique pour réduire la latence du réseau et la surcharge de trafic en centralisant le contrôle et l'orchestration du réseau dans une seule couche de contrôleur SDN. La dernière contribution introduit une approche d'apprentissage en profondeur qui combine SDN et blockchain pour réaliser la planification et le déchargement des tâches, améliorer le taux de réponse des services IoT pour offrir des niveaux de performance élevés et s'efforcer d'effectuer une gestion dynamique des ressources
Deep Reinforcement Learning for energy-aware task offloading in join SDN-Blockchain 5G massive IoT edge network
No full textInternational audienceThe Internet-of-Things (IoT) edge allows cloud computing services for topology and location-sensitive distributed computing. As an immediate benefit, it improves network reliability and latency by enabling data access and processing rapidly and efficiently near IoT devices. However, it comes with several issues stemming from the complexity, the security, the energy consumption, and the instability due to the decentralization of service localization. Furthermore, the multi-resource allocation and task scheduling make this task the furthest from being straightforward. Blockchain has been envisioned to enforce trustworthiness in diverse IoT environments. However, high latency and high energy costs are incurred to process IoT transactions. This paper introduces a novel Blockchain-based Deep Reinforcement Learning (DRL) approach to enable energy-aware task scheduling and offloading in an Software Defined Networking (SDN)-enabled IoT network. The Asynchronous Actor-Critic Agent (A3C) DRL-based policy achieves efficient task scheduling and offloading. The latter is in symbiosis with Proof-of-Authority Blockchain consensus to validate IoT transactions and blocks. By doing so, we improve reliability and low latency and achieve energy efficiency for SDNenabled IoT networks. The A3C policy combined with the Blockchain is proved theoretically. Carried out experiments put forth that our approach offers 50% better energy efficiency, which outperforms traditional consensus algorithms, i.e., Proof of Work and PBFT, in terms of throughput and network latency and offers better scheduling performance.</div
Optimizing Joint Data and Power Transfer in Energy Harvesting Multiuser Wireless Networks
No full textEnergy harvesting emerges as a potential solution for prolonging the lifetime of the energy-constrained mobile wireless devices. In this paper, we focus on radio frequency (RF) energy harvesting for multiuser multicarrier mobile wireless networks. Specifically, we propose joint data and energy transfer optimization frameworks for powering mobile wireless devices through RF energy harvesting. We introduce a power utility that captures the power consumption cost at the base station (BS) and the used power from the users' batteries, and determine optimal power resource allocations that meet data rate requirements of downlink and uplink communications. Two types of harvesting capabilities are considered at each user: harvesting only from dedicated RF signals and hybrid harvesting from both dedicated and ambient RF signals. The developed frameworks increase the end users' battery lifetime at the cost of a slight increase in the BS power consumption. Several evaluation studies are conducted in order to validate our proposed frameworks. 1 2017 IEEE.Manuscript received August 25, 2016; revised February 16, 2017 and May 9, 2017; accepted June 9, 2017. Date of publication June 22, 2017; date of current version December 14, 2017. This work was supported by the National Priorities Research Program under Grant NPRP 5-319-2-121 from the Qatar National Research Fund (a member of Qatar Foundation). The review of this paper was coordinated by Prof. Y. Li. (Corresponding author: Bassem Khalfi.) B. Khalfi and B. Hamdaoui are with Oregon State University, Corvallis, OR 97331 USA (e-mail: [email protected]; [email protected]. edu).Scopu
Uncomputability in Information Theory
No full textWe present a powerful approach for learning about uncomputability and undecidability in informationtheory. Our approach is to use automata from automata theory that have undecidable properties toconstruct channels for which an information-theoretic quantity is uncomputable or undecidable. Wedemonstrate this approach by showing that, for channels with memory, capacity is uncomputable andinformation-stability is undecidable
Repair of damaged end regions of prestressed concrete girders using fiber reinforced polymer composite materials
No full textOver the past couple decades, fiber reinforced polymer (FRP) composites have emerged as a lightweight and efficient repair and retrofit material for many concrete infrastructure applications. FRP can be applied to concrete using many techniques, but primarily as either externally bonded laminates or near-surface mounted (NSM) bars or plates. These repair methods have been shown to be effective when used to provide supplemental flexural and shear reinforcement for reinforced concrete and prestressed concrete beams. One problem afflicting bridge girders in cold climates is the deterioration of the girder ends due to deicing salt exposure, thus reducing their shear strength. This thesis presents the results of the beginning stages of an Illinois Department of Transportation (IDOT) sponsored study to use FRP materials to repair and retrofit the damaged ends of prestressed concrete beams.
In the first phase of the study, direct shear pull-out tests on glass-FRP (GFRP) and carbon-FRP (CFRP) externally bonded laminate and NSM bar concrete specimens are performed. An accelerated aging scheme consisting of freeze/thaw cycling in the presence of a deicing salt solution is implemented to determine the effect of long-term environmental exposure on the FRP/concrete interface. In the next phase, three-point bending tests are performed on small scale prestressed concrete beams. End region deterioration is simulated by imposing damage to the cover concrete, and mortar and FRP repairs are applied to test their effectiveness. Finally, a 3D finite element (FE) model of a full scale prestressed concrete (PC) I-girder is used to investigate the effect of damage to the cover concrete and stirrups in the end region of the girder. Parametric studies are performed using externally bonded CFRP shear laminates to determine the most effective repair schemes for the damaged end region. The results of the shear pull-out tests of CFRP laminates that have undergone accelerated aging are used to calibrate a bond stress-slip model for the interface between the FRP and concrete substrate and approximate the reduced bond stress-slip properties associated with exposure to the environment that causes this type of end region damage. The results of this study indicate the potential for FRP repairs to be an effective means of recovering the original strength of PC bridge girders with damaged end regions, even after environmental aging.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-05-01The student, Ian Shaw, accepted the attached license on 2017-04-27 at 14:28.The student, Ian Shaw, submitted this Thesis for approval on 2017-04-27 at 14:32.This Thesis was approved for publication on 2017-04-27 at 18:48.DSpace SAF Submission Ingestion Package generated from Vireo submission #11118 on 2017-08-10 at 15:07:14Made available in DSpace on 2017-08-10T20:33:31Z (GMT). No. of bitstreams: 3
SHAW-THESIS-2017.pdf: 34368389 bytes, checksum: e0540d2494ba0a646269e92471dbef91 (MD5)
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Previous issue date: 2017-04-27Embargo set by: Colleen Fallaw for item 102853
Lift date: 2019-08-10T21:27:21Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 102853 on 2019-08-11T09:15:39Z
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