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A genetic algorithm for the design of a fuzzy controller for active queue management
Active queue management (AQM) policies are those
policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the
hosts on the network borders, and the adoption of a suitable control
policy. This paper proposes the adoption of a fuzzy proportional
integral (FPI) controller as an active queue manager for Internet
routers. The analytical design of the proposed FPI controller is
carried out in analogy with a proportional integral (PI) controller,
which recently has been proposed for AQM. A genetic algorithm is
proposed for tuning of the FPI controller parameters with respect
to optimal disturbance rejection. In the paper the FPI controller
design metodology is described and the results of the comparison
with random early detection (RED), tail drop, and PI controller
are presented
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A management architecture for active networks
In this paper we present an architecture for network and applications management, which is based on the Active Networks paradigm and shows the advantages of network programmability. The stimulus to develop this architecture arises from an actual need to manage a cluster of active nodes, where it is often required to redeploy network assets and modify nodes connectivity. In our architecture, a remote front-end of the managing entity allows the operator to design new network topologies, to check the status of the nodes and to configure them. Moreover, the proposed framework allows to explore an active network, to monitor the active applications, to query each node and to install programmable traps. In order to take advantage of the Active Networks technology, we introduce active SNMP-like MIBs and agents, which are dynamic and programmable. The programmable management agents make tracing distributed applications a feasible task. We propose a general framework that can inter-operate with any active execution environment. In this framework, both the manager and the monitor front-ends communicate with an active node (the Active Network Access Point) through the XML language. A gateway service performs the translation of the queries from XML to an active packet language and injects the code in the network. We demonstrate the implementation of an active network gateway for PLAN (Packet Language for Active Networks) in a forty active nodes testbed. Finally, we discuss an application of the active management architecture to detect the causes of network failures by tracing network events in time
MESENCHYMAL STEM CELLS IN PH-NEGATIVE MYELOPROLIFERATIVE NEOPLASMS: IDLE OBSERVERS OR PART OF THE DISEASE?
Calibration of material parameters for the Chang-Mander model for unconfined concrete
The current basic OpenSees distribution includes several uniaxial models for concrete. Among them, the model proposed by Chang and Mander in 1994 offers a comprehensive setting applicable both to confined and unconfined concrete, by a proper selection of material parameters. The model offers the possibility to smoothly combine Tsai equation, for the first part of the curve, with a linear branch for the final part. This option is useful to model spalling of unconfined concrete while keeping the smoothness of the curve.
Two basic parameters of the Chang-Mander model for compression, denoted by n and r, govern initial and post-peak stiffness of the Tsai equation, respectively. Besides them, there is a further parameter, denoted by α, which received less attention in the literature and determines the position of the switch between nonlinear and linear parts of the curve.
In the first part of this work, the calibration of the parameters n and r is discussed in some detail. In the second part, the problem of the calibration of α is analyzed. Changes in the value of α may produce large variations in the evaluation of the spalling strain for unconfined concrete. After some comparative analyses with existing models, a simple expression to calibrate α parameter is finally proposed
DEFAULT MODE NETWORK AND WORKING MEMORY NETWORK DURING AN FMRI WORKING MEMORY TASK: DIFFERENCES AND CORRELATIONS WITH BEHAVIORAL PERFORMANCE
INTRODUCTION
Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation[1-5]. However, the mechanism through which working memory load modulates brain connectivity is still unclear. During a working memory task, two of the most involved networks are the default mode network (DMN) and the working memory network (WMN)[6-7]: the selective focus on these networks can be useful in better understanding the load effects. Spatial independent component analysis (ICA)[8] has becomes a reliable technique to investigate the networks involved during an fMRI task, as it extracts spatiotemporal patterns of neural activity maximizing spatial independence. A specific study, conducted with ICA, investigating on how the load and phase of a working memory task are related with the activation and response time, is nowadays lacking. The aim of this work is to use the time course of DMN and WMN, selected by means of ICA, for studying: a) how these networks are involved with the complexity of the task and the phase; b) how, in these networks, complexity and phase are correlated with reaction times. METHODS
MR Data Acquisition and preprocessing
Fifteen young adult healthy and right-handed were involved. The MR protocol consisted of one anatomical sequence 3D T1-weighted MP-RAGE (Voxel size: 1 x 1 x 1 mm) and three functional acquisitions of 15 minutes each performed with a T2*-weighted EPI sequence (TR/TE: 1500/30, In- plane resolution: 3.5x3.5 mm, Thickness: 3.5 mm, Nr of slices: 24, Field of view: 64 x 64 mm). All the images were collected with a Siemens Allegra 3T MR scanner (Siemens, Erlangen, Germany) and a standard head coil. During the fMRI acquisition the subjects performed a delayed spatial working memory paradigm presented with three levels of difficulty. The memory set consisted of one, three or five circles presented randomly in different locations and to the subjects were asked to judge whether or not a given target stimulus had been part of a previous memory stimulus set. Every experiment consisted of 90 working memory trials, 30 per load, divided in three runs. Data were analyzed with Brain Voyager QX. 2.4 (Brain Innovation, Maastricht, The Netherlands). FMRI preprocessing included: 3D head-motion correction, slice-scan time correction, spatial smoothing, temporal high pass filter and linear trend removal. Anatomic 3D data set was inhomogeneities corrected, filtered and transformed into Talairach coordinates and coregistered with the functional information.
Independent Component Analysis
This analysis was conducted using Brainvoyager QX 2.4. ICA analysis was performed on each subject\u2019s three functional acquisitions. A subsequent total ICA group analysis[9-10] was achieved by an inter- subject ICA group analysis of all the intra-subject ICA group analysis. From the obtained maps were selected two Independent Components (ICs) containing the WMN[1,2]: WMN1 defined by SPL and Precuneus, and WMN2 with DLPFC and IPS (Fig. 1b-c). Also one IC describing the DMN was considered, with PCC, IPL and MPFC (Fig. 1a)[11]. For each run of all the subjects the ICs time course was considered: three time windows of 3TR (4.5s) for each working memory task phase (encode, maintenance and retrieval) were selected taking into account the haemodynamic response by delaying the window of 5 volumes events from the start of every trial. The window time course was corrected for a baseline value. Mean values of the ICs where examined and a subsequent correlation between the mean values and the response time in every trial was estimated. A 3x3 two-way ANOVA on Fisher transformed correlation was conducted to test the variation of loads (load1=less complex, load3=more complex), phases and runs.
Figure 1: Networks selected from ICA analysis (transversal view): (a) DMN, (b) WMN1 (c) WMN2.
RESULTS
Figure 2 exhibits window mean activities and correlations divided for phase and load. DMN mean activity is negative while WMN1-2 mean activities have opposite behaviors regarding the phase, but similar concerning with the complexity (Fig. 2a-c). DMN shows a reduction of the correlation from encode to retrieval, instead of WM1-2 where it grows (Fig. 2d-f). The ANOVA showed significant variation for the phases over all the subjects in WMN1-2, an interaction of the variation of phases and runs in WMN2 and a interaction of phases, runs and loads in DMN. DISCUSSION These findings suggest that working memory networks (WMNs), as isolated by means of IC A, display substantially opposed mean values related to a different areas specialization. WMN1 seems to be more involved in the first part of the mnemonic phase and the amount of this involvement is associated to the trial: the more complicated the task, the higher the activation with respect to baseline. On the other hand, WMN2 increases from the first to the last part of the trial and is probably more involved in the operation of retrieval. In Figure 2e-f it is also shown that in the retrieval there is a stronger correlation between WMN1-2 mean values and the response time probably because this phase is the more complex. DMN exhibits, over all the phases, smaller than zero mean values (due to the task inducted deactivation). In contrast, its correlation has a different trend and increases above zero during the maintenance, probably due to the free thought of this phase. The different behavior of load 3 is probably due to the fact that this type of complexity is totally different from the other two. In conclusion, this study shows that, by means of ICA, it is possible to isolate networks of connected regions and relate their time courses to task phases and behavioral performance. This is a promising approach to advance the understanding of connectivity modulations in several brain networks, including WMNs and DMN
Use of ultrasound elasticity imaging to monitor the response of a primary breast cancer to neoadjuvant chemotherapy in one patient in a pilot study
Response of microchannel plates to single particles and to electromagnetic showers
We report on the response of microchannel plates (MCPs) to single
relativistic particles and to electromagnetic showers. Particle detection by
means of secondary emission of electrons at the MCP surface has long been
proposed and is used extensively in ion time-of-flight mass spectrometers. What
has not been investigated in depth is their use to detect the ionizing
component of showers. The time resolution of MCPs exceeds anything that has
been previously used in calorimeters and, if exploited effectively, could aid
in the event reconstruction at high luminosity colliders. Several prototypes of
photodetectors with the amplification stage based on MCPs were exposed to
cosmic rays and to 491 MeV electrons at the INFN-LNF Beam-Test Facility. The
time resolution and the efficiency of the MCPs are measured as a function of
the particle multiplicity, and the results used to model the response to
high-energy showers.Comment: Paper submitted to NIM
Hardware prototyping and validation of a W-ΔDOR digital signal processor
Microwave tracking, usually performed by on ground processing of the signals coming from a spacecraft, represents a crucial aspect in every deep-space mission. Various noise sources, including receiver noise, affect these signals, limiting the accuracy of the radiometric measurements obtained from the radio link. There are several methods used for spacecraft tracking, including the Delta-Differential One-Way Ranging (ΔDOR) technique. In the past years, European Space Agency (ESA) missions relied on a narrowband ΔDOR system for navigation in the cruise phase. To limit the adverse effect of nonlinearities in the receiving chain, an innovative wideband approach to ΔDOR measurements has recently been proposed. This work presents the hardware implementation of a new version of the ESA X/Ka Deep Space Transponder based on the new tracking technique named Wideband ΔDOR (W-ΔDOR). The architecture of the new transponder guarantees backward compatibility with narrowband ΔDOR
OpenSeesPy-based web application for pushover curve computation of RC bridge piers subject to arbitrarily non-uniform corrosion patterns
Existing reinforced concrete (RC) bridge piers are often subject to complex spatially non-uniform steel corrosion patterns typically due to water percolation and exposition to environmental agents. This produces degradation of strength and ductility of the pier, which may significantly influence the seismic performances of bridges. The computation of pushover curves of corroded RC piers can be carried out by fiber-beam-column elements combined with suitable degradation laws for the uniaxial materials. For this purpose, a multi-level fiber-based modeling procedure is proposed based on a partition of the pier into zones characterized by different cross-sections with fiber discretizations reproducing the sectional deterioration pattern.
A web application based on OpenSeesPy is defined to implement this procedure. This includes an interface developed by React JS and Boostrap V5 and an APIs layer based on the Flask framework. Through the interface, users can insert the parameters needed for the structural response simulation, which is, then, performed by employing the numerical procedure developed in Python. At the end of the computation, users can visualize and download the results or vary the input parameters to perform new simulations. The web application runs in a Docker container, making it easy to deploy on cloud platforms or on-premises solutions.
Numerical simulations of real specimens affected by material deterioration are performed
Inotuzumab ozogamicin versus FLAG-Ida in the treatment of relapsed or refractory B-cell acute lymphoblastic leukemia – real-world resource use data
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