630 resultados para threaded posts


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Superseded by its Report: Union Government (Posts and Telegraphs)

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Microcin J25 is a 21 amino acid bacterial peptide that has potent antibacterial activity against Gram-negative bacteria, resulting from its interaction with RNA polymerase. The peptide was previously proposed to have a head-to-tail cyclized peptide backbone and a tight globular structure (Blond, A., Peduzzi, J., Goulard, C., Chiuchiolo, M. J., Barthelemy, M., Prigent, Y., Salomon, R. A., Farias, R. N., Moreno, F. & Rebuffat, S. Eur. J. Biochem. 1999, 259, 747-755). It exhibits remarkable thermal stability for a peptide of its size lacking disulfide bonds and in part this was previously proposed to derive from its macrocyclic structure. We show here that in fact the peptide does not have a head-to-tail cyclic structure but rather a side chain to backbone cyclization between Glu8 and the N-terminus. This creates an embedded ring that is threaded by the C-terminal tail of the molecule, forming a noose-like feature. The three-dimensional structure deduced from NMR data suggests that slippage of the noose is prevented by two aromatic residues flanking the embedded ring. Unthreading does not occur even when the molecule is enzymatically digested with thermolysin. The new structural interpretation fully accounts for previously reported NMR and biophysical data and is consistent with the remarkable stability of this potent antimicrobial peptide.

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In this tutorial paper we summarise the key features of the multi-threaded Qu-Prolog language for implementing multi-threaded communicating agent applications. Internal threads of an agent communicate using the shared dynamic database used as a generalisation of Linda tuple store. Threads in different agents, perhaps on different hosts, communicate using either a thread-to-thread store and forward communication system, or by a publish and subscribe mechanism in which messages are routed to their destinations based on content test subscriptions. We illustrate the features using an auction house application. This is fully distributed with multiple auctioneers and bidders which participate in simultaneous auctions. The application makes essential use of the three forms of inter-thread communication of Qu-Prolog. The agent bidding behaviour is specified graphically as a finite state automaton and its implementation is essentially the execution of its state transition function. The paper assumes familiarity with Prolog and the basic concepts of multi-agent systems.

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This paper is focused on a parallel JAVA implementation of a processor defined in a Network of Evolutionary Processors. Processor description is based on JDom, which provides a complete, Java-based solution for accessing, manipulating, and outputting XML data from Java code. Communication among different processor to obtain a fully functional simulation of a Network of Evolutionary Processors will be treated in future. A safe-thread model of processors performs all parallel operations such as rules and filters. A non-deterministic behavior of processors is achieved with a thread for each rule and for each filter (input and output). Different results of a processor evolution are shown.

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Femtosecond laser microfabrication has emerged over the last decade as a 3D flexible technology in photonics. Numerical simulations provide an important insight into spatial and temporal beam and pulse shaping during the course of extremely intricate nonlinear propagation (see e.g. [1,2]). Electromagnetics of such propagation is typically described in the form of the generalized Non-Linear Schrdinger Equation (NLSE) coupled with Drude model for plasma [3]. In this paper we consider a multi-threaded parallel numerical solution for a specific model which describes femtosecond laser pulse propagation in transparent media [4, 5]. However our approach can be extended to similar models. The numerical code is implemented in NVIDIA Graphics Processing Unit (GPU) which provides an effitient hardware platform for multi-threded computing. We compare the performance of the described below parallel code implementated for GPU using CUDA programming interface [3] with a serial CPU version used in our previous papers [4,5]. © 2011 IEEE.

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We describe a parallel multi-threaded approach for high performance modelling of wide class of phenomena in ultrafast nonlinear optics. Specific implementation has been performed using the highly parallel capabilities of a programmable graphics processor. © 2011 SPIE.

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This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in the context of a project-based learning scenario run on our eMUSE platform. Data is collected from six student cohorts, from six consecutive installments of the Web Applications Design course, comprising of 343 students. A significant model was obtained by relying on the textual complexity and longitudinal analysis indices, applied on the English contributions of 148 students that were actively involved in the undertaken projects.

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Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.

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Poster presented at the “From Basic Sciences to Clinical Research” - First International Congress of CiiEM. Caparica, Portugal, 27-28 November 2015

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Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo topics from the messages that they repost or reply. Our model captures the different extents that leader and follower messages may contain the key topical words, thus further enhances the quality of the induced topics. The results of thorough experiments demonstrate the effectiveness of our proposed model.