985 resultados para Signal conditioning circuits
Resumo:
A field oriented control (FOC) algorithm is simulated and implemented for use with a permanent magnet synchronous motor (PMSM). Rotor position is sensed using Hall effect switches on the stator because other hardware position sensors attached to the rotor may not be desirable or cost effective for certain applications. This places a limit on the resolution of position sensing – only a few Hall effect switches can be placed. In this simulation, three sensors are used and the position information is obtained at higher resolution by estimating it from the rotor dynamics, as shown in literature previously. This study compares the performance of the method with an incremental encoder using simulations. The FOC algorithm is implemented using Digital Motor Control (DMC) and IQ Texas Instruments libraries from a Simulink toolbox called Embedded Coder, and downloaded into a TI microcontroller (TMS320F28335) known as the Piccolo via Code Composer Studio (CCS).
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Novel computer vision techniques have been developed to automatically detect unusual events in crowded scenes from video feeds of surveillance cameras. The research is useful in the design of the next generation intelligent video surveillance systems. Two major contributions are the construction of a novel machine learning model for multiple instance learning through compressive sensing, and the design of novel feature descriptors in the compressed video domain.
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The stop-signal paradigm is increasingly being used as a probe of response inhibition in basic and clinical neuroimaging research. The critical feature of this task is that a cued response is countermanded by a secondary ‘stop-signal’ stimulus offset from the first by a ‘stop-signal delay’. Here we explored the role of task difficulty in the stop-signal task with the hypothesis that what is critical for successful inhibition is the time available for stopping, that we define as the difference between stop-signal onset and the expected response time (approximated by reaction time from previous trial). We also used functional magnetic resonance imaging (fMRI) to examine how the time available for stopping affects activity in the putative right inferior frontal gyrus and presupplementary motor area (right IFG-preSMA) network that is known to support stopping. While undergoing fMRI scanning, participants performed a stop-signal variant where the time available for stopping was kept approximately constant across participants, which enabled us to compare how the time available for stopping affected stop-signal task difficulty both within and between subjects. Importantly, all behavioural and neuroimaging data were consistent with previous findings. We found that the time available for stopping distinguished successful from unsuccessful inhibition trials, was independent of stop-signal delay, and affected successful inhibition depending upon individual SSRT. We also found that right IFG and adjacent anterior insula were more strongly activated during more difficult stopping. These findings may have critical implications for stop-signal studies that compare different patient or other groups using fixed stop-signal delays.
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Inhibitory control deficits are well documented in schizophrenia, supported by impairment in an established measure of response inhibition, the stop-signal reaction time (SSRT). We investigated the neural basis of this impairment by comparing schizophrenia patients and controls matched for age, sex and education on behavioural, functional magnetic resonance imaging (fMRI) and event-related potential (ERP) indices of stop-signal task performance. Compared to controls, patients exhibited slower SSRT and reduced right inferior frontal gyrus (rIFG) activation, but rIFG activation correlated with SSRT in both groups. Go stimulus and stop-signal ERP components (N1/P3) were smaller in patients, but the peak latencies of stop-signal N1 and P3 were also delayed in patients, indicating impairment early in stop-signal processing. Additionally, response-locked lateralised readiness potentials indicated response preparation was prolonged in patients. An inability to engage rIFG may predicate slowed inhibition in patients, however multiple spatiotemporal irregularities in the networks underpinning stop-signal task performance may contribute to this deficit.
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Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).
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Electrochemical aptamer-based (E-AB) sensors represent an emerging class of recently developed sensors. However, numerous of these sensors are limited by a low surface density of electrode-bound redox-oligonucleotides which are used as probe. Here we propose to use the concept of electrochemical current rectification (ECR) for the enhancement of the redox signal of E-AB sensors. Commonly, the probe-DNA performs a change in conformation during target binding and enables a nonrecurring charge transfer between redox-tag and electrode. In our system, the redox-tag of the probe-DNA is continuously replenished by solution-phase redox molecules. A unidirectional electron transfer from electrode via surface-linked redox-tag to the solution-phase redox molecules arises that efficiently amplifies the current response. Using this robust and straight-forward strategy, the developed sensor showed a substantial signal amplification and consequently improved sensitivity with a calculated detection limit of 114 nM for ATP, which was improved by one order of magnitude compared with the amplification-free detection and superior to other previous detection results using enzymes or nanomaterials-based signal amplification. To the best of our knowledge, this is the first demonstration of an aptamer-based electrochemical biosensor involving electrochemical rectification, which can be presumably transferred to other biomedical sensor systems.
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This paper investigates how Enterprise Architecture (EA) evolves due to emerging trends. It specifically explores how EA integrates the Service-oriented Architecture (SOA). Archer’s Morphogenetic theory is used as an analytical approach to distinguish the architectural conditions under which SOA is introduced, to study the relationships between these conditions and SOA introduction, and to reflect on EA evolution (elaborations) that then take place. The paper focuses on reasons for why EA evolution could take place, or not and what architectural changes could happen due to SOA integration. The research builds on sound theoretical foundations to discuss EA evolution in a field that often lacks a solid theoretical groundwork. Specifically, it proposes that critical realism, using the morphogenetic theory, can provide a useful theoretical foundation to study enterprise architecture (EA) evolution. The initial results of a literature review (a-priori model) were extended using explorative interviews. The findings of this study are threefold. First, there are five different levels of EA-SOA integration outcomes. Second, a mature EA, flexible and well-defined EA framework and comprehensive objectives of EA improve the integration outcomes. Third, the analytical separation using Archer’s theory is helpful in order to understand how these different integration outcomes are generated.
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Techniques are presented for enhancing weak Raman scattering signals for rapid yet accurate substance detection. Novel surfaces that allow signal enhancement quantification are described as are eye-safe methodologies that maximize the stand-off Raman detection range.
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We compare three alternative methods for eliciting retrospective confidence in the context of a simple perceptual task: the Simple Confidence Rating (a direct report on a numerical scale), the Quadratic Scoring Rule (a post-wagering procedure), and the Matching Probability (MP; a generalization of the no-loss gambling method). We systematically compare the results obtained with these three rules to the theoretical confidence levels that can be inferred from performance in the perceptual task using Signal Detection Theory (SDT). We find that the MP provides better results in that respect. We conclude that MP is particularly well suited for studies of confidence that use SDT as a theoretical framework.
Resumo:
Opioids are important endogenous ligands that exist in both invertebrates and vertebrates and signal by activation of opioid receptors to produce analgesia and reward or pleasure. The μ-opioid receptor is the best known of the opioid receptors and mediates the acute analgesic effects of opiates, while the δ-opioid receptor (DOR) has been less well studied and has been linked to effects that follow from chronic use of opiates such as stress, inflammation and anxiety. Recently, DORs have been shown to play an essential role in emotions and increasing evidence points to a role in learning actions and outcomes. The process of learning and memory in addiction has been proposed to involve strengthening of specific brain circuits when a drug is paired with a context or environment. The DOR is highly expressed in the hippocampus, amygdala, striatum and other basal ganglia structures known to participate in learning and memory. In this review, we will focus on the role of the DOR and its potential role in learning and memory underlying the development of addiction.
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As the key neuron-to-neuron interface, the synapse is involved in learning and memory, including traumatic memories during times of stress. However, the signal transduction mechanisms by which stress mediates its lasting effects on synapse transmission and on memory are not fully understood. A key component of the stress response is the increased secretion of adrenal steroids. Adrenal steroids (e.g., cortisol) bind to genomic mineralocorticoid and glucocorticoid receptors (gMRs and gGRs) in the cytosol. In addition, they may act through membrane receptors (mMRs and mGRs), and signal transduction through these receptors may allow for rapid modulation of synaptic transmission as well as modulation of membrane ion currents. mMRs increase synaptic and neuronal excitability; mechanisms include the facilitation of glutamate release through extracellular signal-regulated kinase signal transduction. In contrast, mGRs decrease synaptic and neuronal excitability by reducing calcium currents through N-methyl-D-aspartate receptors and voltage-gated calcium channels by way of protein kinase A- and G protein-dependent mechanisms. This body of functional data complements anatomical evidence localizing GRs to the postsynaptic membrane. Finally, accumulating data also suggest the possibility that mMRs and mGRs may show an inverted U-shaped dose response, whereby glutamatergic synaptic transmission is increased by low doses of corticosterone acting at mMRs and decreased by higher doses acting at mGRs. Thus, synaptic transmission is regulated by mMRs and mGRs, and part of the stress signaling response is a direct and bidirectional modulation of the synapse itself by adrenal steroids.
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The lateral amygdala (LA) receives information from auditory and visual sensory modalities, and uses this information to encode lasting memories that predict threat. One unresolved question about the amygdala is how multiple memories, derived from different sensory modalities, are organized at the level of neuronal ensembles. We previously showed that fear conditioning using an auditory conditioned stimulus (CS) was spatially allocated to a stable topography of neurons within the dorsolateral amygdala (LAd) (Bergstrom et al, 2011). Here, we asked how fear conditioning using a visual CS is topographically organized within the amygdala. To induce a lasting fear memory trace we paired either an auditory (2 khz, 55 dB, 20 s) or visual (1 Hz, 0.5 s on/0.5 s off, 35 lux, 20 s) CS with a mild foot shock unconditioned stimulus (0.6 mA, 0.5 s). To detect learning-induced plasticity in amygdala neurons, we used immunohistochemistry with an antibody for phosphorylated mitogen-activated protein kinase (pMAPK). Using a principal components analysis-based approach to extract and visualize spatial patterns, we uncovered two unique spatial patterns of activated neurons in the LA that were associated with auditory and visual fear conditioning. The first spatial pattern was specific to auditory cued fear conditioning and consisted of activated neurons topographically organized throughout the LAd and ventrolateral nuclei (LAvl) of the LA. The second spatial pattern overlapped for auditory and visual fear conditioning and was comprised of activated neurons located mainly within the LAvl. Overall, the density of pMAPK labeled cells throughout the LA was greatest in the auditory CS group, even though freezing in response to the visual and auditory CS was equivalent. There were no differences detected in the number of pMAPK activated neurons within the basal amygdala nuclei. Together, these results provide the first basic knowledge about the organizational structure of two different fear engrams within the amygdala and suggest they are dissociable at the level of neuronal ensembles within the LA