154 resultados para Hand-off


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Several logic gates and switches can be accessed from two different combinations of a single set of fluorophore, receptor and spacer components.

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Posterior parietal cortex (PPC) constitutes a critical cortical node in the sensorimotor system in which goal-directed actions are computed. This information then must be transferred into commands suitable for hand movements to the primary motor cortex (M1). Complexity arises because reach-to-grasp actions not only require directing the hand towards the object (transport component), but also preshaping the hand according to the features of the object (grip component). Yet, the functional influence that specific PPC regions exert over ipsilateral M1 during the planning of different hand movements remains unclear in humans. Here we manipulated transport and grip components of goal-directed hand movements and exploited paired-pulse transcranial magnetic stimulation (ppTMS) to probe the functional interactions between M1 and two different PPC regions, namely superior parieto-occipital cortex (SPOC) and the anterior region of the intraparietal sulcus (aIPS), in the left hemisphere. We show that when the extension of the arm is required to contact a target object, SPOC selectively facilitates motor evoked potentials, suggesting that SPOC-M1 interactions are functionally specific to arm transport. In contrast, a different pathway, linking the aIPS and ipsilateral M1, shows enhanced functional connections during the sensorimotor planning of grip. These results support recent human neuroimaging findings arguing for specialized human parietal regions for the planning of arm transport and hand grip during goal-directed actions. Importantly, they provide new insight into the causal influences these different parietal regions exert over ipsilateral motor cortex for specific types of planned hand movements

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The European Union has set a target of 20% for the share of renewable energy sources in gross final energy consumption in 2020. These renewable energy targets are priority objectives for the Europe 2020 strategy for inclusive growth. In line with the European Union renewable energy policies, the Northern Ireland Executive has a target to deliver 40% renewable electricity by 2020. Currently, Northern Ireland imports 98% of the energy it uses in the form of fossil fuels. Locally produced energy and electricity is needed to ensure sustainable development. The aim of this research is to develop part of a strategy for the mechanical power take-off system for a flap type wave energy converter. Aquamarine Power Ltd’s Oyster flap was the device used for simulation and testing purposes. In this paper the state-of-the-art of wave energy converters is reviewed and a 40th scale test model was developed and built.

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Distinct neural populations carry signals from short-wave (S) cones. We used individual differences to test whether two types of pathways, those that receive excitatory input (S+) and those that receive inhibitory input (S-), contribute independently to psychophysical performance. We also conducted a genome-wide association study (GWAS) to look for genetic correlates of the individual differences. Our psychophysical test was based on the Cambridge Color Test, but detection thresholds were measured separately for S-cone spatial increments and decrements. Our participants were 1060 healthy adults aged 16-40. Test-retest reliabilities for thresholds were good (ρ=0.64 for S-cone increments, 0.67 for decrements and 0.73 for the average of the two). "Regression scores," isolating variability unique to incremental or decremental sensitivity, were also reliable (ρ=0.53 for increments and ρ=0.51 for decrements). The correlation between incremental and decremental thresholds was ρ=0.65. No genetic markers reached genome-wide significance (p-7). We identified 18 "suggestive" loci (p-5). The significant test-retest reliabilities show stable individual differences in S-cone sensitivity in a normal adult population. Though a portion of the variance in sensitivity is shared between incremental and decremental sensitivity, over 26% of the variance is stable across individuals, but unique to increments or decrements, suggesting distinct neural substrates. Some of the variability in sensitivity is likely to be genetic. We note that four of the suggestive associations found in the GWAS are with genes that are involved in glucose metabolism or have been associated with diabetes.

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Patients in perioperative healthcare settings are at risk of acquiring or developing infections because of the performance of invasive procedures. Serious life threatening infections can arise when micro-organisms are transmitted onto susceptible sites, such as: surgical wounds or intravascular cannulation sites. Infection control practices help to protect patients and healthcare providers by reducing and/or eliminating sources of infection.

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Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

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Ambisonics and Higher Order Ambisonics (HOA) are scalable spatial audio techniques that attempt to present a sound scene to listeners over as large an area as possible. A localisation experiment was carried out to investigate the performance of a first and third order system at three listening positions - one in the centre and two off-centre - using a 5 m radius loudspeaker array. The results are briefly presented and compared to those of an earlier experiment on a 2.2 m loudspeaker array. In both experiments the off-centre listeners were placed such that the ratio of distance from the centre to the array radius was constant in both experiments. The test used a reverse target-pointer adjustment method to determine the error, both signed and absolute, for each combination of listening position and system. The results for both arrays were found to be very similar, suggesting that the relative amplitude of the loudspeakers, which were the same in both cases, was more dominant for localisation than the arrival time differences, which differed between array sizes.

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Power dissipation and tolerance to process variations pose conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor up-sizing for process tolerance can be detrimental for power dissipation. However, for certain signal processing systems such as those used in color image processing, we noted that effective trade-offs can be achieved between Vdd scaling, process tolerance and "output quality". In this paper we demonstrate how these tradeoffs can be effectively utilized in the development of novel low-power variation tolerant architectures for color interpolation. The proposed architecture supports a graceful degradation in the PSNR (Peak Signal to Noise Ratio) under aggressive voltage scaling as well as extreme process variations in. sub-70nm technologies. This is achieved by exploiting the fact that some computations are more important and contribute more to the PSNR improvement compared to the others. The computations are mapped to the hardware in such a way that only the less important computations are affected by Vdd-scaling and process variations. Simulation results show that even at a scaled voltage of 60% of nominal Vdd value, our design provides reasonable image PSNR with 69% power savings.