981 resultados para reactive navigation system


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Response inhibition is the ability to suppress inadequate but automatically activated, prepotent or ongoing response tendencies. In the framework of motor inhibition, two distinct operating strategies have been described: “proactive” and “reactive” control modes. In the proactive modality, inhibition is recruited in advance by predictive signals, and actively maintained before its enactment. Conversely, in the reactive control mode, inhibition is phasically enacted after the detection of the inhibitory signal. To date, ample evidence points to a core cerebral network for reactive inhibition comprising the right inferior frontal gyrus (rIFG), the presupplementary motor area (pre-SMA) and the basal ganglia (BG). Moreover, fMRI studies showed that cerebral activations during proactive and reactive inhibition largely overlap. These findings suggest that at least part of the neural network for reactive inhibition is recruited in advance, priming cortical regions in preparation for the upcoming inhibition. So far, proactive and reactive inhibitory mechanisms have been investigated during tasks in which the requested response to be stopped or withheld was an “overt” action execution (AE) (i.e., a movement effectively performed). Nevertheless, inhibitory mechanisms are also relevant for motor control during “covert actions” (i.e., potential motor acts not overtly performed), such as motor imagery (MI). MI is the conscious, voluntary mental rehearsal of action representations without any overt movement. Previous studies revealed a substantial overlap of activated motor-related brain networks in premotor, parietal and subcortical regions during overtly executed and imagined movements. Notwithstanding this evidence for a shared set of cerebral regions involved in encoding actions, whether or not those actions are effectively executed, the neural bases of motor inhibition during MI, preventing covert action from being overtly performed, in spite of the activation of the motor system, remain to be fully clarified. Taking into account this background, we performed a high density EEG study evaluating cerebral mechanisms and their related sources elicited during two types of cued Go/NoGo task, requiring the execution or withholding of an overt (Go) or a covert (MI) action, respectively. The EEG analyses were performed in two steps, with different aims: 1) Analysis of the “response phase” of the cued overt and covert Go/NoGo tasks, for the evaluation of reactive inhibitory control of overt and covert actions. 2) Analysis of the “preparatory phase” of the cued overt and covert Go/NoGo EEG datasets, focusing on cerebral activities time-locked to the preparatory signals, for the evaluation of proactive inhibitory mechanisms and their related neural sources. For these purposes, a spatiotemporal analysis of the scalp electric fields was applied on the EEG data recorded during the overt and covert Go/NoGo tasks. The spatiotemporal approach provide an objective definition of time windows for source analysis, relying on the statistical proof that the electric fields are different and thus generated by different neural sources. The analysis of the “response phase” revealed that key nodes of the inhibitory circuit, underpinning inhibition of the overt movement during the NoGo response, were also activated during the MI enactment. In both cases, inhibition relied on the activation of pre-SMA and rIFG, but with different temporal patterns of activation in accord with the intended “covert” or “overt” modality of motor performance. During the NoGo condition, the pre-SMA and rIFG were sequentially activated, pointing to an early decisional role of pre-SMA and to a later role of rIFG in the enactment of inhibitory control of the overt action. Conversely, a concomitant activation of pre-SMA and rIFG emerged during the imagined motor response. This latter finding suggested that an inhibitory mechanism (likely underpinned by the rIFG), could be prewired into a prepared “covert modality” of motor response, as an intrinsic component of the MI enactment. This mechanism would allow the rehearsal of the imagined motor representations, without any overt movement. The analyses of the “preparatory phase”, confirmed in both overt and covert Go/NoGo tasks the priming of cerebral regions pertaining to putative inhibitory network, reactively triggered in the following response phase. Nonetheless, differences in the preparatory strategies between the two tasks emerged, depending on the intended “overt” or “covert” modality of the possible incoming motor response. During the preparation of the overt Go/NoGo task, the cue primed the possible overt response programs in motor and premotor cortex. At the same time, through preactivation of a pre-SMA-related decisional mechanism, it triggered a parallel preparation for the successful response selection and/or inhibition during the subsequent response phase. Conversely, the preparatory strategy for the covert Go/NoGo task was centred on the goal-oriented priming of an inhibitory mechanism related to the rIFG that, being tuned to the instructed covert modality of the motor performance and instantiated during the subsequent MI enactment, allowed the imagined response to remain a potential motor act. Taken together, the results of the present study demonstrate a substantial overlap of cerebral networks activated during proactive recruitment and subsequent reactive enactment of motor inhibition in both overt and covert actions. At the same time, our data show that preparatory cues predisposed ab initio a different organization of the cerebral areas (in particular of the pre-SMA and rIFG) involved with sensorimotor transformations and motor inhibitory control for executed and imagined actions. During the preparatory phases of our cued overt and covert Go/NoGo tasks, the different adopted strategies were tuned to the “how” of the motor performance, reflecting the intended overt and covert modality of the possible incoming action.

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Reactive power is critical to the operation of the power networks on both safety aspects and economic aspects. Unreasonable distribution of the reactive power would severely affect the power quality of the power networks and increases the transmission loss. Currently, the most economical and practical approach to minimizing the real power loss remains using reactive power dispatch method. Reactive power dispatch problem is nonlinear and has both equality constraints and inequality constraints. In this thesis, PSO algorithm and MATPOWER 5.1 toolbox are applied to solve the reactive power dispatch problem. PSO is a global optimization technique that is equipped with excellent searching capability. The biggest advantage of PSO is that the efficiency of PSO is less sensitive to the complexity of the objective function. MATPOWER 5.1 is an open source MATLAB toolbox focusing on solving the power flow problems. The benefit of MATPOWER is that its code can be easily used and modified. The proposed method in this thesis minimizes the real power loss in a practical power system and determines the optimal placement of a new installed DG. IEEE 14 bus system is used to evaluate the performance. Test results show the effectiveness of the proposed method.

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SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

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"Report no. CG-D-47-80."

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Final report, issued Feb. 1977.

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Mode of access: Internet.

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Bill Chappell, Jr., chairman, Subcommittee on Defense, Committee on Appropriations, House of Representatives. -- p. [1].

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Includes index.

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This study demonstrates the effectiveness of a novel self-adjuvanting vaccine delivery system for multiple different synthetic peptide immunogens by use of lipid core peptide (LCP) technology. An LCP formulation incorporating two different protective epitopes of the surface antiphagocytic M protein of group A streptococci (GAS)-the causative agents of rheumatic fever and subsequent rheumatic heart disease-was tested in a murine parenteral immunization and GAS challenge model. Mice were immunized with the LCP-GAS formulation, which contains an M protein amino-terminal type-specific peptide sequence (8830) in combination with a conserved non-host-cross-reactive carboxy-terminal C-region peptide sequence (J8) of the M protein. Our data demonstrated immunogenicity of the LCP-8830-J8 formulation in B10.BR mice when coadministered in complete Freund's adjuvant and in the absence of a conventional adjuvant. In both cases, immunization led to induction of high-titer GAS peptide-specific serum immunoglobulin G antibody responses and induction of highly opsonic antibodies that did not cross-react with human heart tissue proteins. Moreover, mice were completely protected from GAS infection when immunized with LCP-8830-J8 in the presence or absence of a conventional adjuvant. Mice were not protected, however, following immunization with an LCP formulation containing a control peptide from a Schistosoma sp. These data support the potential of LCP technology in the development of novel self-adjuvanting multi-antigen component vaccines and point to the potential application of this system in the development of human vaccines against infectious diseases.

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Although the importance of CD4(+) T cell responses to human cytonnegalovirus (HCMV) has recently been recognized in transplant and immunosuppressed patients, the precise specificity and nature of this response has remained largely unresolved. In the present study we have isolated CD4(+) CTL which recognize epitopes from HCMV glycoproteins gB and gH in association with two different HLA-DR antigens, DRA1*0101/DRB1*0701 (DR7) and DRA1*0101/DRB1*1101 (DR11). Comparison of amino acid sequences of HICMV isolates revealed that the gB and gH epitope sequences recognized by human CD4(+) T cells were not only conserved in clinical isolates from HCMV but also in CMV isolates from higher primates (chimpanzee, rhesus and baboon). Interestingly, these epitope sequences from chimpanzee, rhesus and baboon CMV are efficiently recognized by human CD4(+) CTL. More importantly, we show that gB-specific T cells from humans can also efficiently lyse pepticle-sensitized Patr-DR7(+) cells from chimpanzees. These findings suggest that conserved gB and gH epitopes should be considered while designing a prophylactic vaccine against HCMV. In addition, they also provide a functional basis for the conservation of MHC class 11 lineages between humans and Old World primates and open the possibility for the use of such primate models in vaccine development against HCMV.