Long-term uncertainty quantification in WRF-modeled offshore wind resource off the US Atlantic coast

Uncertainty quantification of long-term modeled wind speed is essential to ensure stakeholders can best leverage wind resource numerical data sets. Offshore, this need is even stronger given the limited availability of observations of wind speed at heights relevant for wind energy purposes and the resulting heavier relative weight of numerical data sets for wind energy planning and operational projects. In this analysis, we consider the National Renewable Energy Laboratory's 21-year updated numerical offshore data set for the US East Coast and provide a methodological framework to leverage both floating lidar and near-surface buoy observations in the region to quantify uncertainty in the modeled hub-height wind resource. We first show how using a numerical ensemble to quantify the uncertainty in modeled wind speed is insufficient to fully capture the model deviation from real-world observations. Next, we train and validate a random forest to vertically extrapolate near-surface wind speed to hub height using the available short-term lidar data sets in the region. We then apply this model to vertically extrapolate the long-term near-surface buoy wind speed observations to hub height so that they can be directly compared to the long-term numerical data set. We find that the mean 21-year uncertainty in 140 m hourly average wind speed is slightly lower than 3 m s−1 (roughly 30 % of the mean observed wind speed) across the considered region. Atmospheric stability is strictly connected to the modeled wind speed uncertainty, with stable conditions associated with an uncertainty which is, on average, about 20 % larger than the overall mean uncertainty.</p

Asymmetry index in muscle activations

Gait asymmetry is typically evaluated using spatio-temporal or joint kinematics parameters. Only a few studies addressed the problem of defining an asymmetry index directly based on muscle activity, extracting parameters from surface electromyography (sEMG) signals. Moreover, no studies used the extraction of the muscle principal activations (activations that are necessary for accomplishing a specific motor task) as the base to construct an asymmetry index, less affected by the variability of sEMG patterns. The aim of this study is to define a robust index to quantitative assess the asymmetry of muscle activations during locomotion, based on the extraction of the principal activations. SEMG signals were analyzed combining Statistical Gait Analysis (SGA) and a clustering algorithm that allows for obtaining the muscle principal activations. We evaluated the asymmetry levels of four lower limb muscles in: (1) healthy subjects of different ages (children, adults, and elderly); (2) different populations of orthopedic patients (adults with megaprosthesis of the knee after bone tumor resection, elderly subjects after total knee arthroplasty and elderly subjects after total hip arthroplasty); and (3) neurological patients (children with hemiplegic cerebral palsy and elderly subjects affected by idiopathic Normal Pressure Hydrocephalus). The asymmetry index obtained for each pathological population was then compared to that of age-matched controls. We found asymmetry levels consistent with the expected impact of the different pathologies on muscle activation during gait. This suggests that the proposed index can be successfully used in clinics for an objective assessment of the muscle activation asymmetry during locomotion

Wood anatomical traits in black spruce reveal latent water constraints on the boreal forest

The effects of climate change on high-latitude forest ecosystems are complex, making forecasts of future scenarios uncertain. The predicted lengthening of the growing season under warming conditions is expected to increase tree growth rates. However, there is evidence of an increasing sensitivity of the boreal forest to drought stress. To assess the influence of temperature and precipitation on the growth of black spruce (Picea mariana), we investigated long-term series of wood anatomical traits on 20 trees from four sites along 600 km, the latitudinal range of the closed boreal forest in Quebec, Canada. We correlated the anatomical traits resolved at intraring level with daily temperature, vapor pressure deficit (VPD), and precipitation during the 1943\u20132010 period. Tree-ring width, number of cells per ring and cell wall thickness were positively affected by spring and summer daily mean and maximum temperature at the northern sites. These results agree with the well-known positive effect of high temperatures on tree ring formation at high latitudes. However, we captured, for the first time in this region, the latent impact of water availability on xylem traits. Indeed, in all the four sites, cell lumen area showed positive correlations with daily precipitation (mostly at low latitude), and/or negative correlations with daily mean and maximum temperature and VPD (mostly at high latitude). We inferred that drought, due to high temperatures, low precipitations, or both, negatively af- fects cell enlargement across the closed boreal forest, including the northernmost sites. The production of tracheids with narrower lumen, potentially more resistant to cavitation, could increase xylem hydraulic safety under a warmer and drier cli- mate. However, this would result in lower xylem conductivity, with consequent long- term hydraulic deterioration, growth decline, and possibly lead to tree dieback, as observed in other forest ecosystems at lower latitude

Longitudinal assessment of muscle function after Total Hip Arthroplasty : Use of clustering to extract principal activations from EMG signals

Statistical gait analysis (SGA) is a powerful method to quantitatively assess the muscle function during locomotion. Nevertheless, the problem of dataset comparison is still very challenging when considering EMG gait signals. Aim of this study was to cope with the problem of EMG dataset comparison by extracting principal activations through the CIMAP algorithm. In particular, we analyzed and compared EMG gait data of 20 hip prosthesis patients at 3, 6 and 12 months after surgery and 20 matched control subjects. The information obtained provides a compact description of the muscle activation patters in the analyzed populations. The proposed approach can be useful to clinicians for easily comparing different populations and/or different time points evaluations from the same population (follow-up)