314 resultados para Phases Dynamic Balancer


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Because moving depictions of face emotion have greater ecological validity than their static counterparts, it has been suggested that still photographs may not engage ‘authentic’ mechanisms used to recognize facial expressions in everyday life. To date, however, no neuroimaging studies have adequately addressed the question of whether the processing of static and dynamic expressions rely upon different brain substrates. To address this, we performed an functional magnetic resonance imaging (fMRI) experiment wherein participants made emotional expression discrimination and Sex discrimination judgements to static and moving face images. Compared to Sex discrimination, Emotion discrimination was associated with widespread increased activation in regions of occipito-temporal, parietal and frontal cortex. These regions were activated both by moving and by static emotional stimuli, indicating a general role in the interpretation of emotion. However, portions of the inferior frontal gyri and supplementary/pre-supplementary motor area showed task by motion interaction. These regions were most active during emotion judgements to static faces. Our results demonstrate a common neural substrate for recognizing static and moving facial expressions, but suggest a role for the inferior frontal gyrus in supporting simulation processes that are invoked more strongly to disambiguate static emotional cues.

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Objective: To investigate limb loading and dynamic stability during squatting in the early functional recovery of total hip arthroplasty (THA) patients. Design: Cohort study Setting: Inpatient rehabilitation clinic. Participants: A random sample of 61 THA patients (34♂/27♀; 62±9 yrs, 77±14 kg, 174±9 cm) was assessed twice, 13.2±3.8 days (PRE) and 26.6±3.3 days post-surgery (POST), and compared with a healthy reference group (REF) (22♂/16♀; 47±12yrs; 78±20kg; 175±10cm). Interventions: THA patients received two weeks of standard in-patient rehabilitation. Main Outcome Measure(s): Inter-limb vertical force distribution and dynamic stability during the squat maneuver, as defined by the root mean square (RMS) of the center of pressure in antero-posterior and medio-lateral directions, of operated (OP) and non-operated (NON)limbs. Self-reported function was assessed via FFb-H-OA 2.0 questionnaire. Results: At PRE, unloading of the OP limb was 15.8% greater (P<.001, d=1.070) and antero-posterior and medio-lateral center of pressure RMS were 30-34% higher in THA than REF P<.05). Unloading was reduced by 12.8% towards a more equal distribution from PRE to POST (P<.001, d=0.874). Although medio-lateral stability improved between PRE and POST (OP: 14.8%, P=.024, d=0.397; NON: 13.1%, P=.015, d=0.321), antero-posterior stability was not significantly different. Self-reported physical function improved by 15.8% (P<.001, d=0.965). Conclusion(s): THA patients unload the OP limb and are dynamically more unstable during squatting in the early rehabilitation phase following total hip replacement than healthy adults. Although loading symmetry and medio-lateral stability improved to the level of healthy adults with rehabilitation, antero-posterior stability remained impaired. Measures of dynamic stability and load symmetry during squatting provide quantitative information that can be used to clinically monitor early functional recovery from THA.

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The development of offshore oil and gas fields require the placement of different equipment on the sea floor. This is done by deploying the equipment from vessels operating in dynamic positioning on the surface. The deployment operation has different phases, and in higher sea states, it may require wave-load synchronization, when the load is going through the splash zone, and heave compensation when the load is close to the sea floor. In this paper, we analyse the performance of a particular type of hardware operating in a heave compensation mode. We derive a comprehensive model, analyse limits of performance and evaluate a control strategy.

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As a social species in a constantly changing environment, humans rely heavily on the informational richness and communicative capacity of the face. Thus, understanding how the brain processes information about faces in real-time is of paramount importance. The N170 is a high temporal resolution electrophysiological index of the brain's early response to visual stimuli that is reliably elicited in carefully controlled laboratory-based studies. Although the N170 has often been reported to be of greatest amplitude to faces, there has been debate regarding whether this effect might be an artifact of certain aspects of the controlled experimental stimulation schedules and materials. To investigate whether the N170 can be identified in more realistic conditions with highly variable and cluttered visual images and accompanying auditory stimuli we recorded EEG 'in the wild', while participants watched pop videos. Scene-cuts to faces generated a clear N170 response, and this was larger than the N170 to transitions where the videos cut to non-face stimuli. Within participants, wild-type face N170 amplitudes were moderately correlated to those observed in a typical laboratory experiment. Thus, we demonstrate that the face N170 is a robust and ecologically valid phenomenon and not an artifact arising as an unintended consequence of some property of the more typical laboratory paradigm.

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With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

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Schizophrenia patients have been shown to be compromised in their ability to recognize facial emotion. This deficit has been shown to be related to negative symptoms severity. However, to date, most studies have used static rather than dynamic depictions of faces. Nineteen patients with schizophrenia were compared with seventeen controls on 2 tasks; the first involving the discrimination of facial identity, emotion, and butterfly wings; the second testing emotion recognition using both static and dynamic stimuli. In the first task, the patients performed more poorly than controls for emotion discrimination only, confirming a specific deficit in facial emotion recognition. In the second task, patients performed more poorly in both static and dynamic facial emotion processing. An interesting pattern of associations suggestive of a possible double dissociation emerged in relation to correlations with symptom ratings: high negative symptom ratings were associated with poorer recognition of static displays of emotion, whereas high positive symptom ratings were associated with poorer recognition of dynamic displays of emotion. However, while the strength of associations between negative symptom ratings and accuracy during static and dynamic facial emotion processing was significantly different, those between positive symptom ratings and task performance were not. The results confirm a facial emotion-processing deficit in schizophrenia using more ecologically valid dynamic expressions of emotion. The pattern of findings may reflect differential patterns of cortical dysfunction associated with negative and positive symptoms of schizophrenia in the context of differential neural mechanisms for the processing of static and dynamic displays of facial emotion.

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While the neural regions associated with facial identity recognition are considered to be well defined, the neural correlates of non-moving and moving images of facial emotion processing are less clear. This study examined the brain electrical activity changes in 26 participants (14 males M = 21.64, SD = 3.99; 12 females M = 24.42, SD = 4.36), during a passive face viewing task, a scrambled face task and separate emotion and gender face discrimination tasks. The steady state visual evoked potential (SSVEP) was recorded from 64-electrode sites. Consistent with previous research, face related activity was evidenced at scalp regions over the parieto-temporal region approximately 170 ms after stimulus presentation. Results also identified different SSVEP spatio-temporal changes associated with the processing of static and dynamic facial emotions with respect to gender, with static stimuli predominately associated with an increase in inhibitory processing within the frontal region. Dynamic facial emotions were associated with changes in SSVEP response within the temporal region, which are proposed to index inhibitory processing. It is suggested that static images represent non-canonical stimuli which are processed via different mechanisms to their more ecologically valid dynamic counterparts.

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Academic and professional staff at Queensland University of Technology (QUT) have been faced with the challenge of how to create engaging student experiences in collaborative learning spaces. In 2013 a new Bachelor of Science course was implemented focusing on inquiry-based, collaborative and active learning. Student groups in two of the first year units carried out a poster assessment task. This paper provides a preliminary evaluation of the assessment approach used, whereby students created dynamic digital posters to capitalise on the affordances of the learning space.

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In this paper, we present a dynamic model to identify influential users of micro-blogging services. Micro-blogging services, such as Twitter, allow their users (twitterers) to publish tweets and choose to follow other users to receive tweets. Previous work on user influence on Twitter, concerns more on following link structure and the contents user published, seldom emphasizes the importance of interactions among users. We argue that, by emphasizing on user actions in micro-blogging platform, user influence could be measured more accurately. Since micro-blogging is a powerful social media and communication platform, identifying influential users according to user interactions has more practical meanings, e.g., advertisers may concern how many actions – buying, in this scenario – the influential users could initiate rather than how many advertisements they spread. By introducing the idea of PageRank algorithm, innovatively, we propose our model using action-based network which could capture the ability of influential users when they interacting with micro-blogging platform. Taking the evolving prosperity of micro-blogging into consideration, we extend our actionbaseduser influence model into a dynamic one, which could distinguish influential users in different time periods. Simulation results demonstrate that our models could support and give reasonable explanations for the scenarios that we considered.

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This study tests Teece’s conceptualization of dynamic capabilities in the context of small and medium sized firms competing in creative industries, i.e. the European audio-visual production industry. This industry is characterized by immature and evolving markets where firms’ dynamic capabilities are expected to lead to superior innovative performance. Using survey data from audio-visual producers in ten European countries we find that both sensing and seizing capabilities have a positive effect on firms' innovative performance. The effect however, is curvilinear and positive effects appear only when capabilities overcome a threshold level.

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Carbon fibre reinforced polymer (CFRP) strengthening of metallic structures under static loading has shown great potential in the recent years. However, steel structures are often experienced natural (e.g. earthquake, wind) as well as man-made (e.g. vehicular impact, blast) dynamic loading. Therefore, there is a growing interest among the researchers to investigate the capability of CFRP strengthened members under such dynamic conditions. This study focuses on the finite element (FE) numerical modelling and simulation of CFRP strengthened steel column under transverse impact loading to predict the behaviour and failure modes. Impact simulation process and the CFRP strengthened steel column are validated with the existing experimental results in literature. The validated FE model of CFRP strengthened steel column is then further used to investigate the effects of transverse impact loading on its structural performance. The results are presented in terms of transvers e impact force, lateral and axial displacement, and deformed shape to evaluate the effectiveness of CFRP strengthening technique. Comparisons between the bare steel and CFRP strengthened steel columns clearly indicate the performance enhancement of strengthened column under transverse impact loading.

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Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.

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Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.

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