Enhanced Mid -Infrared Reflectance with Graphene Coated Silicon Carbide Nanowires

© 2020 IEEE. The mid-infrared optical spectrum hosts a variety of promising photonic applications. Herein we simulate and experimentally demonstrate reflectance enhancement of MIR light using graphene-coated silicon carbide nanowires on silicon, showing promise for on-chip MIR Nano photonics

Muscle size and strength : debunking the “completely separate phenomena” suggestion

This is a post-peer-review, pre-copyedit version of an article published in European Journal of Applied Physiology. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00421-017-3616-

Enhanced absorption with graphene-coated silicon carbide nanowires for mid-infrared nanophotonics

The mid-infrared (MIR) is an exciting spectral range that also hosts useful molecular vi-brational fingerprints. There is a growing interest in nanophotonics operating in this spectral range, and recent advances in plasmonic research are aimed at enhancing MIR infrared nanophotonics. In particular, the design of hybrid plasmonic metasurfaces has emerged as a promising route to realize novel MIR applications. Here we demonstrate a hybrid nanostructure combining graphene and silicon carbide to extend the spectral phonon response of silicon carbide and enable absorption and field enhancement of the MIR photon via the excitation and hybridization of surface plasmon po-laritons and surface phonon polaritons. We combine experimental methods and finite element sim-ulations to demonstrate enhanced absorption of MIR photons and the broadening of the spectral resonance of graphene-coated silicon carbide nanowires. We also indicate subwavelength confinement of the MIR photons within a thin oxide layer a few nanometers thick, sandwiched between the graphene and silicon carbide. This intermediate shell layer is characteristically obtained using our graphitization approach and acts as a coupling medium between the core and outer shell of the nanowires

Non-invasive estimation of muscle fibre size from high-density electromyography

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity could be a non-invasive index of muscle fibre size in humans. However, the relation between motor unit conduction velocity and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e. high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e. muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. We demonstrate the possibility of predicting muscle fibre diameter (R2 = 0.66) and cross-sectional area (R2 = 0.65) from conduction velocity estimates with low systematic bias (∼2% and ∼4% respectively) and a relatively low margin of individual error (∼8% and ∼16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, ageing, space and exercise physiology, although the applicability and validity of the proposed methodology need to be more directly assessed in these specific populations by future studies

Modelling suppressed muscle activation by means of an exponential sigmoid function: Validation and bounds

This article was accepted for publication in the Journal of Biomechanics [© Elsevier Ltd.] and the definitive version is available at: http://dx.doi.org/10.1016/j.jbiomech.2015.01.009The aim of this study was to establish how well a three-parameter sigmoid exponential function, DIFACT, follows experimentally obtained voluntary neural activation-angular velocity profiles and how robust it is to perturbed levels of maximal activation. Six male volunteers (age 26.3±2.73 years) were tested before and after an 8-session, 3-week training protocol. Torque–angular velocity (T–ω) and experimental voluntary neural drive–angular velocity (%VA–ω) datasets, obtained via the interpolated twitch technique, were determined from pre- and post-training testing sessions. Non-linear regression fits of the product of DIFACT and a Hill type tetanic torque function and of the DIFACT function only were performed on the pre- and post-training T–ω and %VA–ω datasets for three different values of the DIFACT upper bound, αmax, 100%, 95% & 90%. The determination coefficients, R2, and the RMS of the fits were compared using a two way mixed ANOVA and results showed that there was no significant difference (p<0.05) due to changing αmax values indicating the DIFACT remains robust to changes in maximal activation. Mean R2 values of 0.95 and 0.96 for pre- and post-training sessions show that the maximal voluntary torque function successfully reproduces the T–ω raw dataset

Changes in agonist neural drive, hypertrophy and pre-training strength all contribute to the individual strength gains after resistance training.

PURPOSE: Whilst neural and morphological adaptations following resistance training (RT) have been investigated extensively at a group level, relatively little is known about the contribution of specific physiological mechanisms, or pre-training strength, to the individual changes in strength following training. This study investigated the contribution of multiple underpinning neural [agonist EMG (QEMGMVT), antagonist EMG (HEMGANTAG)] and morphological variables [total quadriceps volume (QUADSVOL), and muscle fascicle pennation angle (QUADSθ p)], as well as pre-training strength, to the individual changes in strength after 12 weeks of knee extensor RT. METHODS: Twenty-eight healthy young men completed 12 weeks of isometric knee extensor RT (3/week). Isometric maximum voluntary torque (MVT) was assessed pre- and post-RT, as were simultaneous neural drive to the agonist (QEMGMVT) and antagonist (HEMGANTAG). In addition QUADSVOL was determined with MRI and QUADSθ p with B-mode ultrasound. RESULTS: Percentage changes (∆) in MVT were correlated to ∆QEMGMVT (r = 0.576, P = 0.001), ∆QUADSVOL (r = 0.461, P = 0.014), and pre-training MVT (r = -0.429, P = 0.023), but not ∆HEMGANTAG (r = 0.298, P = 0.123) or ∆QUADSθ p (r = -0.207, P = 0.291). Multiple regression analysis revealed 59.9% of the total variance in ∆MVT after RT to be explained by ∆QEMGMVT (30.6%), ∆QUADSVOL (18.7%), and pre-training MVT (10.6%). CONCLUSIONS: Changes in agonist neural drive, quadriceps muscle volume and pre-training strength combined to explain the majority of the variance in strength changes after knee extensor RT (~60%) and adaptations in agonist neural drive were the most important single predictor during this short-term intervention

Multiple perspectives on the attribution of the extreme European summer of 2012 to climate change

Summer 2012 was very wet in northern Europe, and unusually dry and hot in southern Europe. We use multiple approaches to determine whether anthropogenic forcing made the extreme European summer of 2012 more likely. Using a number of observation- and model-based methods, we find that there was an anthropogenic contribution to the extremes in southern Europe, with a qualitative consensus across all methodologies. There was a consensus across the methodologies that there has been a significant increase in the risk of hot summers in southern Europe with climate change. Most approaches also suggested a slight drying, but none of the results were statistically significant. The unusually wet summer in northern Europe was made more likely by the observed atmospheric circulation pattern in 2012, but no evidence was found for a long-term trend in circulation

Attribution of 2012 extreme climate events: does air-sea interaction matter?

In 2012, extreme anomalous climate conditions occurred around the globe. Large areas of North America experienced an anomalously hot summer, with large precipitation deficits inducing severe drought. Over Europe, the summer of 2012 was marked by strong precipitation anomalies with the UK experiencing its wettest summer since 1912 while Spain suffered severe drought. What caused these extreme climate conditions in various regions in 2012? This study compares attribution conclusions for 2012 climate anomalies relative to a baseline period (1964–1981) based on two sets of parallel experiments with different model configurations (with coupling to an ocean mixed layer model or with prescribed sea surface temperatures) to assess whether attribution conclusions concerning the climate anomalies in 2012 are sensitive to the representation of air-sea interaction. Modelling results indicate that attribution conclusions for large scale surface air temperature (SAT) changes in both boreal winter and summer are generally robust and not very sensitive to air-sea interaction. This is especially true over southern Europe, Eurasia, North America, South America, and North Africa. Some other responses also appear to be insensitive to air-sea interaction: for example, forced increases in precipitation over northern Europe and Sahel, and reduced precipitation over North America and the Amazon in boreal summer. However, the attribution of circulation and precipitation changes for some other regions exhibits a sensitivity to air-sea interaction. Results from the experiments including coupling to an ocean mixed layer model show a positive NAO-like circulation response in the Atlantic sector in boreal winter and weak changes in the East Asian summer monsoon and precipitation over East Asia. With prescribed sea surface temperatures, some different responses arise over these two regions. Comparison with observed changes indicates that the coupled simulations generally agree better with observations, demonstrating that attribution methods based on atmospheric general circulation models have limitations and may lead to erroneous attribution conclusions for regional anomalies in circulation, precipitation and surface air temperature