985 resultados para background traffic load
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Background and purpose: The present study reports on the preparation and testing of a sustained delivery system for the immunomodulatory peptide P10 aimed at reducing the in vivo degradation of the peptide and the amount required to elicit a protective immune response against paracoccidioidomycosis. Experimental approach: BALB/c mice were infected with the yeast Paracoccidioides brasiliensis to mimic the chronic form of paracoccidioidomycosis. The animals were treated daily with sulfamethoxazole/trimethoprim alone or combined with peptide P10, either emulsified in Freund`s adjuvant or entrapped in poly(lactic acid-glycolic acid) (PLGA) nanoparticles at different concentrations (1 mu g, 5 mu g, 10 mu g, 20 mu g or 40 mu g center dot 50 mu L-1). Therapeutic efficacy was assessed as fungal burden in tissues and the immune response by quantitative determination of cytokines. Key results: Animals given combined chemotherapy and P10 nanotherapy presented a marked reduction of fungal load in the lungs, compared with the non-treated animals. After 30 days of treatment, P10 entrapped within PLGA (1 mu g center dot 50 mu L-1) was more effective than `free` P10 emulsified in Freund`s adjuvant (20 mu g center dot 50 mu L-1), as an adjuvant to chemotherapy. After treatment for 90 days, the higher doses of P10 entrapped within PLGA (5 or 10 mu g center dot 50 mu L-1) were most effective. Treatment with P10 emulsified in Freund`s adjuvant (20 mu g center dot 50 mu L-1) or P10 entrapped within PLGA (1 mu g center dot 50 mu L-1) were accompanied by high levels of interferon-gamma in lung. Conclusions and implications: Combination of sulfamethoxazole/trimethoprim with the P10 peptide entrapped within PLGA demonstrated increased therapeutic efficacy against paracoccidioidomycosis. P10 incorporation into PLGA nanoparticles dramatically reduced the peptide amount necessary to elicit a protective effect.
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Background. Periodontal diseases (PDs) are infectious diseases in which periodontopathogens trigger chronic inflammatory and immune responses that lead to tissue destruction. Recently, viruses have been implicated in the pathogenesis of PDs. Individuals infected with human T lymphotropic virus 1 (HTLV-1) present with abnormal oral health and a marked increased prevalence of periodontal disease. Methods. In this study, we investigated the patterns of periodontopathogen infection and local inflammatory immune markers in HTLV-1-seropositive individuals with chronic periodontitis (CP/HTLV-1 group) compared with HTLV-1 -seronegative individuals with chronic periodontitis (CP group) and periodontally healthy, HTLV-1 -seronegative individuals (control group). Results. Patients in the CP/HTLV-1 group had significantly higher values of bleeding on probing, mean probing depth, and attachment loss than patients in the CP group. The expression of tumor necrosis factor a and interleukin (IL) 4 was found to be similar in the CP and CP/HTLV-1 groups, whereas IL-12 and IL-17 levels trended toward a higher expression in the CP/HTLV-1 group. A significant increase was seen in the levels of IL-1 beta and interferon gamma in the CP/HTLV-1 group compared with the CP group, whereas expression of the regulatory T cell marker FOXp3 and IL-10 was significantly decreased in the lesions from the CP/HTLV-1 group. Interestingly, similar frequency and/or load of periodontopathogens (Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, and Aggregatibacter actinomycetemcomitans) and frequency of viruses (herpes simplex virus 1, human cytomegalovirus, and Epstein-Barr virus) characteristically associated with PDs were found in the CP/HTLV and CP groups. Conclusions. HTLV-1 may play a critical role in the pathogenesis of periodontal disease through the deregulation of the local cytokine network, resulting in an exacerbated response against a standard periodontopathogen infection.
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Background and Objective: Inflammatory cytokines such as tumor necrosis factor-alpha are involved in the pathogenesis of periodontal diseases. A high between-subject variation in the level of tumor necrosis factor-alpha mRNA has been verified, which may be a result of genetic polymorphisms and/or the presence of periodontopathogens such as Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola (called the red complex) and Aggregatibacter actinomycetemcomitans. In this study, we investigated the effect of the tumor necrosis factor-alpha (TNFA) -308G/A gene polymorphism and of periodontopathogens on the tumor necrosis factor-alpha levels in the periodontal tissues of nonsmoking patients with chronic periodontitis (n = 127) and in control subjects (n = 177). Material and Methods: The TNFA-308G/A single nucleotide polymorphism was investigated using polymerase chain reaction-restriction fragment length polymorphism analysis, whereas the tumor necrosis factor-alpha levels and the periodontopathogen load were determined using real-time polymerase chain reaction. Results: No statistically significant differences were found in the frequency of the TNFA-308 single nucleotide polymorphism in control and chronic periodontitis groups, in spite of the higher frequency of the A allele in the chronic periodontitis group. The concomitant analyses of genotypes and periodontopathogens demonstrated that TNFA-308 GA/AA genotypes and the red-complex periodontopathogens were independently associated with increased levels of tumor necrosis factor-alpha in periodontal tissues, and no additive effect was seen when both factors were present. P. gingivalis, T. forsythia and T. denticola counts were positively correlated with the level of tumor necrosis factor-alpha. TNFA-308 genotypes were not associated with the periodontopathogen detection odds or with the bacterial load. Conclusion: Our results demonstrate that the TNFA-308 A allele and red-complex periodontopathogens are independently associated with increased levels of tumor necrosis factor-alpha in diseased tissues of nonsmoking chronic periodontitis patients and consequently are potentially involved in determining the disease outcome.
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Path-integral representations for a scalar particle propagator in non-Abelian external backgrounds are derived. To this aim, we generalize the procedure proposed by Gitman and Schvartsman of path-integral construction to any representation of SU(N) given in terms of antisymmetric generators. And for arbitrary representations of SU(N), we present an alternative construction by means of fermionic coherent states. From the path-integral representations we derive pseudoclassical actions for a scalar particle placed in non-Abelian backgrounds. These actions are classically analyzed and then quantized to prove their consistency.
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We present a method to determine the magnitude of the uncorrelated background distribution obtained with the event mixing technique, through the simultaneous observation of the projectile elastic scattering in different detectors, which correspond to random coincidences. The procedure is tested with alpha-d angular correlation data from the (6)Li + (59)Co reaction at E(lab) = 29.6 MeV. We also show that the method can be applied using the product of singles events, when singles measurements are available. (C) 2009 Elsevier B.V. All rights reserved.
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We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.
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Background: The rat has been a mainstay of physiological and metabolic research, and more recently mice. This study aimed at characterizing the postprandial triglyceride profile of two members of the Muridae family: the Wistar rats (Rattus norvegicus albinus) and C57BL/6 mice (Mus musculus) plus comparing them to the profile obtained in humans. Methods: Thirty-one male and twelve female Wistar rats, ten C57BL/6 male and nine female mice received a liquid meal containing fat (17%), protein (4%) and carbohydrates (4%), providing 2 g fat/Kg. Thirty-one men and twenty-nine women received a standardized liquid meal containing fat (25%), dextromaltose (55%), protein (14%), and vitamins and minerals (6%), and providing 40 g of fat per square meter of body surface. Serial blood samples were collected at 2, 4, 6, 8 and 10 h after the ingestion in rats, at 1, 2, 3, 4, 5 and 6 h in mice and in humans at 2, 4, 6 and 8 h. Wilcoxon and Mann-Whitney tests were used. Results/Discussion: The triglyceride responses were evaluated after the oral fat loads. Fasting and postprandial triglyceridemia were determined sequentially in blood sample. AUC, AUIC, AR, RR and late peaks were determined. Conclusions: Rats are prone to respond in a pro-atherogenic manner. The responses in mice were closer to the ones in healthy men. This study presents striking differences in postprandial triglycerides patterns between rats and mice not correlated to baseline triglycerides, the animal baseline body weight or fat load in all animal groups.
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Multiple sclerosis (MS) is a progressive inflammatory and/or demyelinating disease of the human central nervous system (CNS). Most of the knowledge about the pathogenesis of MS has been derived from murine models, such as experimental autoimmune encephalomyelitis and vital encephalomyelitis. Here, we infected female C57BL/6 mice with a neurotropic strain of the mouse hepatitis virus (MHV-59A) to evaluate whether treatment with the multifunctional antioxidant tempol (4-hydroxy-2,2,6,6-tetramethyl-1-piperidinyloxy) affects the ensuing encephalomyelitis. In untreated animals, neurological symptoms developed quickly: 90% of infected mice died 10 days after virus inoculation and the few survivors presented neurological deficits. Treatment with tempol (24 mg/kg, ip, two doses on the first day and daily doses for 7 days plus 2 mM tempol in the drinking water ad libitum) profoundly altered the disease outcome: neurological symptoms were attenuated, mouse survival increased up to 70%, and half of the survivors behaved as normal mice. Not Surprisingly, tempol substantially preserved the integrity of the CNS, including the blood-brain barrier. Furthermore, treatment with tempol decreased CNS vital titers, macrophage and T lymphocyte infiltration, and levels of markers of inflammation, such as expression of inducible nitric oxide synthase, transcription of tumor necrosis factor-alpha and interferon-gamma, and protein nitration. The results indicate that tempol ameliorates murine viral encephalomyelitis by altering the redox status of the infectious environment that contributes to an attenuated CNS inflammatory response. overall, our study supports the development of therapeutic strategies based on nitroxides to manage neuroinflammatory diseases, including MS. (C) 2009 Elsevier Inc. All rights reserved.
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Catalysts with various nickel loads were prepared on supports of ZrO2, ZrO2-Y2O3 and ZrO2-CaO, characterized by XRD and TPR and tested for activity in ethanol steam reforming. XRD of the supports identified the monoclinic crystalline phase in the ZrO2 and cubic phases in the ZrO2-Y2O3 and ZrO2-CaO supports. In the catalysts, the nickel impregnated on the supports was identified as the NiO phase. In the TPR analysis, peaks were observed showing the NiO phase having different interactions with the supports. In the catalytic tests, practically all the catalysts achieved 100% ethanol conversion, H-2 yield was near 70% and the gaseous concentrations of the other co-products varied in accordance with the equilibrium among them, affected principally by the supports. It was observed that when the ZrO2 was modified with Y2O3 and CaO, there were big changes in the CO and CO2 concentrations, which were attributed to the rise in the number of oxygen vacancies, permitting high-oxygen mobility and affecting the gaseous equilibrium. The liquid products analysis showed a low selectivity to liquid co-products during the reforming reactions. (c) 2007 Published by Elsevier B.V.
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Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.
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The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.
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Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB).IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth datatransmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] First, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one incontinuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be include CAC, traffic policing used for traffic control.QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator andanalytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.
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IPTV is now offered by several operators in Europe, US and Asia using broadcast video over private IP networks that are isolated from Internet. IPTV services rely ontransmission of live (real-time) video and/or stored video. Video on Demand (VoD)and Time-shifted TV are implemented by IP unicast and Broadcast TV (BTV) and Near video on demand are implemented by IP multicast. IPTV services require QoS guarantees and can tolerate no more than 10-6 packet loss probability, 200 ms delay, and 50 ms jitter. Low delay is essential for satisfactory trick mode performance(pause, resume,fast forward) for VoD, and fast channel change time for BTV. Internet Traffic Engineering (TE) is defined in RFC 3272 and involves both capacity management and traffic management. Capacity management includes capacityplanning, routing control, and resource management. Traffic management includes (1)nodal traffic control functions such as traffic conditioning, queue management, scheduling, and (2) other functions that regulate traffic flow through the network orthat arbitrate access to network resources. An IPTV network architecture includes multiple networks (core network, metronetwork, access network and home network) that connects devices (super head-end, video hub office, video serving office, home gateway, set-top box). Each IP router in the core and metro networks implements some queueing and packet scheduling mechanism at the output link controller. Popular schedulers in IP networks include Priority Queueing (PQ), Class-Based Weighted Fair Queueing (CBWFQ), and Low Latency Queueing (LLQ) which combines PQ and CBWFQ.The thesis analyzes several Packet Scheduling algorithms that can optimize the tradeoff between system capacity and end user performance for the traffic classes. Before in the simulator FIFO,PQ,GPS queueing methods were implemented inside. This thesis aims to implement the LLQ scheduler inside the simulator and to evaluate the performance of these packet schedulers. The simulator is provided by ErnstNordström and Simulator was built in Visual C++ 2008 environmentand tested and analyzed in MatLab 7.0 under windows VISTA.
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The purpose of this project is to update the tool of Network Traffic Recognition System (NTRS) which is proprietary software of Ericsson AB and Tsinghua University, and to implement the updated tool to finish SIP/VoIP traffic recognition. Basing on the original NTRS, I analyze the traffic recognition principal of NTRS, and redesign the structure and module of the tool according to characteristics of SIP/VoIP traffic, and then finally I program to achieve the upgrade. After the final test with our SIP data trace files in the updated system, a satisfactory result is derived. The result presents that our updated system holds a rate of recognition on a confident level in the SIP session recognition as well as the VoIP call recognition. In the comparison with the software of Wireshark, our updated system has a result which is extremely close to Wireshark’s output, and the working time is much less than Wireshark. In the aspect of practicability, the memory overflow problem is avoided, and the updated system can output the specific information of SIP/VoIP traffic recognition, such as SIP type, SIP state, VoIP state, etc. The upgrade fulfills the demand of this project.
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With the rapid development of telecommunication industry, the IP multimedia Subsystem (IMS) could very well be the panacea for most telecom operators. It is originally defined as the core network for 3G mobile systems by the 3rd Generation Partnership Project (3GPP), the more recent development is merging between fixed line network and wireless networkd This report researchs the characteristic of the IMS data and proposes an IMS characterization analysis. We captured the IMS traffic data with 10 tousands users for about 41 hours. By analyzing the characteristics of the IMS, we know that the most important application in the IMS is VoIP call. Then we use the tool designed by Tsinghua University & Ericsson Company to recognize the data, and the results we got can be used to build the traffic models. From the results of the traffic models, I will get some reasons and conclusion. The traffic model gives out the types of session and types of VoIP call. I bring into a concept—busy hour. This concept is very important because it can help us to know which period is the peak of the VoIP call. The busy hour is from 10:00 to 11:00 in the morning. I also bring into another concept—connection ratio. This concept is significant because it can evaluate whether the VoIP call is good when it use IMS network. By comparing the traffic model with other one’s models, we found the different results from them, both the accuracy and the busy hour. From the contract, we got the advantages of our traffic models.