898 resultados para Multi-Loop Control
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One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.
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This review describes the ways in which the primary bradycardia and peripheral vasoconstriction evoked by selective stimulation of peripheral chemoreceptors can be modified by the secondary effects of a chemoreceptor-induced increase in ventilation. The evidence that strong stimulation of peripheral chemoreceptors can evoke the behavioural and cardiovascular components of the alerting or defence response which is characteristically evoked by novel or noxious stimuli is considered. The functional significance of all these influences in systemic hypoxia is then discussed with emphasis on the fact that these reflex changes can be overcome by the local effects of hypoxia: central neural hypoxia depresses ventilation, hypoxia acting on the heart causes bradycardia and local hypoxia of skeletal muscle and brain induces vasodilatation. Further, it is proposed that these local influences can become interdependent, so generating a positive feedback loop that may explain sudden infant death syndrome (SIDS). It is also argued that a major contributor to these local influences is adenosine. The role of adenosine in determining the distribution of O2 in skeletal muscle microcirculation in hypoxia is discussed, together with its possible cellular mechanisms of action. Finally, evidence is presented that in chronic systemic hypoxia, the reflex vasoconstrictor influences of the sympathetic nervous system are reduced and/or the local dilator influences of hypoxia are enhanced. In vitro and in vivo findings suggest this is partly explained by upregulation of nitric oxide (NO) synthesis by the vascular endothelium which facilitates vasodilatation induced by adenosine and other NO-dependent dilators and attenuates noradrenaline-evoked vasoconstriction.
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The release of adrenocorticotropin (ACTH) from the corticotrophs is controlled principally by vasopressin and corticotropin-releasing hormone (CRH). Oxytocin may augment the release of ACTH under certain conditions, whereas atrial natriuretic peptide acts as a corticotropin release-inhibiting factor to inhibit ACTH release by direct action on the pituitary. Glucocorticoids act on their receptors within the hypothalamus and anterior pituitary gland to suppress the release of vasopressin and CRH and the release of ACTH in response to these neuropeptides. CRH neurons in the paraventricular nucleus also project to the cerebral cortex and subcortical regions and to the locus ceruleus (LC) in the brain stem. Cortical influences via the limbic system and possibly the LC augment CRH release during emotional stress, whereas peripheral input by pain and other sensory impulses to the LC causes stimulation of the noradrenergic neurons located there that project their axons to the CRH neurons stimulating them by alpha-adrenergic receptors. A muscarinic cholinergic receptor is interposed between the alpha-receptors and nitric oxidergic interneurons which release nitric oxide that activates CRH release by activation of cyclic guanosine monophosphate, cyclooxygenase, lipoxygenase and epoxygenase. Vasopressin release during stress may be similarly mediated. Vasopressin augments the release of CRH from the hypothalamus and also augments the action of CRH on the pituitary. CRH exerts a positive ultrashort loop feedback to stimulate its own release during stress, possibly by stimulating the LC noradrenergic neurons whose axons project to the paraventricular nucleus to augment the release of CRH.
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Genes encoding lipoproteins LipL32, LipL41 and the outer-membrane protein OmpL1 of leptospira were recombined and cloned into a pVAX1 plasmid. BALB/c mice were immunized with LipL32 and recombined LipL32-41-OmpL1 using DNA-DNA, DNA-protein and protein-protein strategies, respectively. Prime immunization was on day 1, boost immunizations were on day 11 and day 21. Sera were collected from each mouse on day 35 for antibody, cytokine detection and microscopic agglutination test while spleen cells were collected for splenocyte proliferation assay. All experimental groups (N = 10 mice per group) showed statistically significant increases in antigen-specific antibodies, in cytokines IL-4 and IL-10, as well as in the microscopic agglutination test and splenocyte proliferation compared with the pVAX1 control group. The groups receiving the recombined LipL32-41-OmpL1 vaccine induced anti-LipL41 and anti-OmpL1 antibodies and yielded better splenocyte proliferation values than the groups receiving LipL32. DNA prime and protein boost immune strategies stimulated more antibodies than a DNA-DNA immune strategy and yielded greater cytokine and splenocyte proliferation than a protein-protein immune strategy. It is clear from these results that recombination of protective antigen genes lipL32, lipL41, and ompL1 and a DNA-protein immune strategy resulted in better immune responses against leptospira than single-component, LipL32, or single DNA or protein immunization.
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The South American sea lion, Otaria flavescens, is widely distributed along the Pacific and Atlantic coasts of South America. However, along the Brazilian coast, there are only two nonbreeding sites for the species (Refúgio de Vida Silvestre da Ilha dos Lobos and Refúgio de Vida Silvestre do Molhe Leste da Barra do Rio Grande), both in Southern Brazil. In this region, the species is continuously under the effect of anthropic activities, mainly those related to environmental contamination with organic and inorganic chemicals and fishery interactions. This paper reports, for the first time, the genetic diversity of O. flavescens found along the Southern Brazilian coast. A 287-bp fragment of the mitochondrial DNA control region (D-loop) was analyzed. Seven novel haplotypes were found in 56 individuals (OFA1-OFA7), with OFA1 being the most frequent (47.54%). Nucleotide diversity was moderate (π = 0.62%) and haplotype diversity was relatively low (67%). Furthermore, the median joining network analysis indicated that Brazilian haplotypes formed a reciprocal monophyletic clade when compared to the haplotypes from the Peruvian population on the Pacific coast. These two populations do not share haplotypes and may have become isolated some time back. Further genetic studies covering the entire species distribution are necessary to better understand the biological implications of the results reported here for the management and conservation of South American sea lions.
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The aim of this thesis is to propose a novel control method for teleoperated electrohydraulic servo systems that implements a reliable haptic sense between the human and manipulator interaction, and an ideal position control between the manipulator and the task environment interaction. The proposed method has the characteristics of a universal technique independent of the actual control algorithm and it can be applied with other suitable control methods as a real-time control strategy. The motivation to develop this control method is the necessity for a reliable real-time controller for teleoperated electrohydraulic servo systems that provides highly accurate position control based on joystick inputs with haptic capabilities. The contribution of the research is that the proposed control method combines a directed random search method and a real-time simulation to develop an intelligent controller in which each generation of parameters is tested on-line by the real-time simulator before being applied to the real process. The controller was evaluated on a hydraulic position servo system. The simulator of the hydraulic system was built based on Markov chain Monte Carlo (MCMC) method. A Particle Swarm Optimization algorithm combined with the foraging behavior of E. coli bacteria was utilized as the directed random search engine. The control strategy allows the operator to be plugged into the work environment dynamically and kinetically. This helps to ensure the system has haptic sense with high stability, without abstracting away the dynamics of the hydraulic system. The new control algorithm provides asymptotically exact tracking of both, the position and the contact force. In addition, this research proposes a novel method for re-calibration of multi-axis force/torque sensors. The method makes several improvements to traditional methods. It can be used without dismantling the sensor from its application and it requires smaller number of standard loads for calibration. It is also more cost efficient and faster in comparison to traditional calibration methods. The proposed method was developed in response to re-calibration issues with the force sensors utilized in teleoperated systems. The new approach aimed to avoid dismantling of the sensors from their applications for applying calibration. A major complication with many manipulators is the difficulty accessing them when they operate inside a non-accessible environment; especially if those environments are harsh; such as in radioactive areas. The proposed technique is based on design of experiment methodology. It has been successfully applied to different force/torque sensors and this research presents experimental validation of use of the calibration method with one of the force sensors which method has been applied to.
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Crystal properties, product quality and particle size are determined by the operating conditions in the crystallization process. Thus, in order to obtain desired end-products, the crystallization process should be effectively controlled based on reliable kinetic information, which can be provided by powerful analytical tools such as Raman spectrometry and thermal analysis. The present research work studied various crystallization processes such as reactive crystallization, precipitation with anti-solvent and evaporation crystallization. The goal of the work was to understand more comprehensively the fundamentals, phenomena and utilizations of crystallization, and establish proper methods to control particle size distribution, especially for three phase gas-liquid-solid crystallization systems. As a part of the solid-liquid equilibrium studies in this work, prediction of KCl solubility in a MgCl2-KCl-H2O system was studied theoretically. Additionally, a solubility prediction model by Pitzer thermodynamic model was investigated based on solubility measurements of potassium dihydrogen phosphate with the presence of non-electronic organic substances in aqueous solutions. The prediction model helps to extend literature data and offers an easy and economical way to choose solvent for anti-solvent precipitation. Using experimental and modern analytical methods, precipitation kinetics and mass transfer in reactive crystallization of magnesium carbonate hydrates with magnesium hydroxide slurry and CO2 gas were systematically investigated. The obtained results gave deeper insight into gas-liquid-solid interactions and the mechanisms of this heterogeneous crystallization process. The research approach developed can provide theoretical guidance and act as a useful reference to promote development of gas-liquid reactive crystallization. Gas-liquid mass transfer of absorption in the presence of solid particles in a stirred tank was investigated in order to gain understanding of how different-sized particles interact with gas bubbles. Based on obtained volumetric mass transfer coefficient values, it was found that the influence of the presence of small particles on gas-liquid mass transfer cannot be ignored since there are interactions between bubbles and particles. Raman spectrometry was successfully applied for liquid and solids analysis in semi-batch anti-solvent precipitation and evaporation crystallization. Real-time information such as supersaturation, formation of precipitates and identification of crystal polymorphs could be obtained by Raman spectrometry. The solubility prediction models, monitoring methods for precipitation and empirical model for absorption developed in this study together with the methodologies used gives valuable information for aspects of industrial crystallization. Furthermore, Raman analysis was seen to be a potential controlling method for various crystallization processes.
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Many, if not all, aspects of our everyday lives are related to computers and control. Microprocessors and wireless communications are involved in our lives. Embedded systems are an attracting field because they combine three key factors, small size, low power consumption and high computing capabilities. The aim of this thesis is to study how Linux communicates with the hardware, to answer the question if it is possible to use an operating system like Debian for embedded systems and finally, to build a Mechatronic real time application. In the thesis a presentation of Linux and the Xenomai real time patch is given, the bootloader and communication with the hardware is analyzed. BeagleBone the evaluation board is presented along with the application project consisted of a robot cart with a driver circuit, a line sensor reading a black line and two Xbee antennas. It makes use of Xenomai threads, the real time kernel. According to the obtained results, Linux is able to operate as a real time operating system. The issue of future research is the area of embedded Linux is also discussed.
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Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.
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Introduction: Les efforts globaux pour contrôler la tuberculose sont présentement restreints par la prévalence croissante du VIH/SIDA. Quoique les éclosions de la tuberculose multi résistante (TB-MDR) soient fréquemment rapportées parmi les populations atteintes du SIDA, le lien entre VIH/SIDA et le développement de résistance n’est pas clair. Objectifs: Cette recherche visait à : (1) développer une base de connaissances concernant les facteurs associés à des éclosions de la TB-MDR parmi les patients atteints du VIH/SIDA; (2) utiliser ce cadre de connaissances pour accroître des mesures préliminaires pour mieux contrôler la tuberculose pulmonaire chez les patients atteints du VIH/SIDA; et (3) afin d’améliorer l’application des ces mesures, affiner les techniques bactériologiques existantes pour Mycobacterium tuberculosis. Méthodologie: Quatre études ont été réalisées : (1) Une étude longitudinale pour identifier les facteurs associés avec une éclosion de la TB-MDR parmi les patients atteints du SIDA qui ont reçu le traitement directement supervisé de courte durée (DOTS) pour la tuberculose pulmonaire au Lima et au Pérou entre 1999 et 2005; (2) Une étude transversale pour décrire différentes étapes de l’histoire naturelle de la tuberculose, la prévalence et les facteurs associés avec la mycobactérie qu’on retrouve dans les selles des patients atteints du SIDA; (3) Un projet pilote pour développer des stratégies de dépistage pour la tuberculose pulmonaire parmi les patients hospitalisés atteints du SIDA, en utilisant l’essaie Microscopic Observation Drug Susceptibility (MODS); et (4) Une étude laboratoire pour identifier les meilleures concentrations critiques pour détecter les souches MDR de M. tuberculosis en utilisant l’essaie MODS. Résultats : Étude 1 démontre qu’une épidémie de TB-MDR parmi les patients atteints du SIDA qui ont reçu DOTS pour la tuberculose pulmonaire ait été causée par la superinfection du clone de M. tuberculosis plutôt que le développement de la résistance secondaire. Bien que ce clone ait été plus commun parmi la cohorte de patients atteints du SIDA, il n’avait aucune différence de risque pour superinfection entre les patients avec ou sans SIDA. Ces résultats suggèrent qu’un autre facteur, possiblement associé à la diarrhée, peu contribuer à la prévalence élevée de ce clone chez les patients atteints du SIDA. Étude 2 suggère que chez la plupart des patients atteints du SIDA il a été retrouvé une mycobactérie dans leurs selles alors qu’ils étaient en phase terminale au niveau de la tuberculose pulmonaire. Or, les patients atteints du SIDA ayant été hospitalisés pendant les deux dernières années pour une autre condition médicale sont moins à risque de se retrouver avec une mycobactérie dans leurs selles. Étude 3 confirme que la tuberculose pulmonaire a été commune à tous les patients hospitalisés atteints du SIDA, mais diagnostiquée incorrectement en utilisant les critères cliniques présentement recommandés pour la tuberculose. Or, l’essaie MODS a détecté pour la plupart de ces cas. De plus, MODS a été également efficace quand la méthode a été dirigée aux patients soupçonnés d’avoir la tuberculose, à cause de leurs symptômes. Étude 4 démontre les difficultés de détecter les souches de M. tuberculosis avec une faible résistance contre ethambutol et streptomycine en utilisant l’essai MODS avec les concentrations de drogue présentement recommandées pour un milieu de culture. Cependant, l’utilité diagnostique de MODS peut être améliorée ; modifier les concentrations critiques et utiliser deux plaques et non une, pour des tests réguliers. Conclusion: Nos études soulèvent la nécessité d’améliorer le diagnostic et le traitement de la tuberculose parmi les patients atteints du SIDA, en particulier ceux qui vivent dans des régions avec moins de ressources. Par ailleurs, nos résultats font ressortir les effets indirects que les soins de santé ont sur les patients infectés par le VIH et qu’ils peuvent avoir sur le développement de la tuberculose.
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Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université de Technologie de Troyes
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Most adaptive linearization circuits for the nonlinear amplifier have a feedback loop that returns the output signal oj'tne eunplifier to the lineurizer. The loop delay of the linearizer most be controlled precisely so that the convergence of the linearizer should be assured lot this Letter a delay control circuit is presented. It is a delay lock loop (ULL) with it modified early-lute gate and can he easily applied to a DSP implementation. The proposed DLL circuit is applied to an adaptive linearizer with the use of a polynomial predistorter, and the simulalion for a 16-QAM signal is performed. The simulation results show that the proposed DLL eliminates the delay between the reference input signal and the delayed feedback signal of the linearizing circuit perfectly, so that the predistorter polynomial coefficients converge into the optimum value and a high degree of linearization is achieved
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We show numerically that direct delayed optoelectronic feedback can suppress hysteresis and bistability in a directly modulated semiconductor laser. The simulation of a laser with feedback is performed for a considerable range of feedback strengths and delays and the corresponding values for the areas of the hysteresis loops are calculated. It is shown that the hysteresis loop completely vanishes for certain combinations of these parameters. The regimes for the disappearance of bistability are classified globally. Different dynamical states of the laser are characterized using bifurcation diagrams and time series plots.
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One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.
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Multi-component reactions are effective in building complex molecules in a single step in a minimum amount of time and with facile isolation procedures; they have high economy1–7 and thus have become a powerful synthetic strategy in recent years.8–10 The multicomponent protocols are even more attractive when carried out in aqueous medium. Water offers several benefits, including control over exothermicity, and the isolation of products can be carried out by single phase separation technique. Pyranopyrazoles are a biologically important class of heterocyclic compounds and in particular dihydropyrano[2,3-c]pyrazoles play an essential role in promoting biological activity and represent an interesting template in medicinal chemistry. Heterocyclic compounds bearing the 4-H pyran unit have received much attention in recent years as they constitute important precursors for promising drugs.11–13 Pyrano[2,3-c]pyrazoles exhibit analgesic,14 anti-cancer,15 anti-microbial and anti-inflammatory16 activity. Furthermore dihydropyrano[2,3-c]pyrazoles show molluscidal activity17,18 and are used in a screening kit for Chk 1 kinase inhibitor activity.19,20 They also find applications as pharmaceutical ingredients and bio-degradable agrochemicals.21–29 Junek and Aigner30 first reported the synthesis of pyrano[2,3-c]pyrazole derivatives from 3-methyl-1-phenylpyrazolin-5-one and tetracyanoethylene in the presence of triethylamine. Subsequently, a number of synthetic approaches such as the use of triethylamine,31 piperazine,32 piperidine,33 N-methylmorpholine in ethanol,34 microwave irradiation,35,36 solvent-free conditions,37–39 cyclodextrins (CDs),40 different bases in water,41 γ -alumina,42 and l-proline43 have been reported for the synthesis of 6-amino-4-alkyl/aryl-3-methyl- 2,4-dihydropyrano[2,3-c]pyrazole-5-carbonitriles. Recently, tetraethylammonium bromide (TEABr) has emerged as mild, water-tolerant, eco-friendly and inexpensive catalyst. To the best of our knowledge, quaternary ammonium salts, more specifically TEABr, have notbeen used as catalysts for the synthesis of pyrano[2,3-c]pyrazoles, and we decided to investigate the application of TEABr as a catalyst for the synthesis of a series of pyrazole-fused pyran derivatives via multi-component reactions