Effect of Mitigation Measures on the Spreading of COVID-19 in Hard-Hit States

State government-mandated social distancing measures have helped to slow down the growth of the COVID-19 pandemic in the United States. Current predictive models of the development of COVID-19, especially after mitigation efforts, are largely based on extrapolating the data from other countries. Since most states enforced stay-at-home orders towards the end of March, their effect should be reflected in the death and infection counts at the end of April. Using the data available until April 25th, we investigate the change in the infection rate due to the mitigation efforts, and project death and infection counts until September, 2020, for some of the most heavily impacted states: New York, New Jersey, Michigan, Massachusetts, Illinois and Louisiana. We find that with the current mitigation efforts five of those six states reduce their reproduction number to a value less than one, stopping the exponential growth of the pandemic. We also projected different scenarios after the mitigation is relaxed. Analysis for other states can be found at https://covid19projection.org/.Comment: 8 pages, 6 figures, 2 table

Identifying structural changes with unsupervised machine learning methods

Unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems

Influence of the biomechanical variables of the gait cycle in running economy. [Influencia de variables biomecánicas del ciclo de paso en la economía de carrera].

<p algn="justify">The aim of this study was to investigate the relationships between biomechanical variables and running economy (RE). Eleven recreational (RR) and 14 well-trained runners (WT) completed 4 min stages on a treadmill at different speeds. During the test, biomechanical variables such as ground contact time (tc), swing time (tsw), stride length, frequency and angle and the length of the different subphases of ground contact were calculated using an optical measurement system. VO2 was measured in order to calculate RE. The WT runners were more economical than the RR at all speeds and presented lower tc, higher tsw, longer strides, lower stride frequencies and higher stride angles (P<0.05). Similarly, the WT runners experienced a later propulsion subphase than the RR runners (P<0.05). RE was positively related to tc, stride frequency and 10-km race pace, whereas it was negatively related to tsw, stride length, stride angle and the propulsive subphase. Our results suggest that running patterns characterized by longer stride lengths and higher stride angles, lower stride frequencies and tc, higher tsw and later propulsion suphases may enable an efficient energy use per stride. </p> Resumen <p align="justify">El objetivo de este estudio fue el investigar las relaciones entre diferentes variables biomecánicas y la economía de carrera (RE). Once atletas populares (RR) y 14 atletas altamente entrenados (WT) completaron estadios de 4 min en tapiz rodante a diferentes velocidades. Durante el test, el tiempo de contacto (tc) y de vuelo (tsw), la longitud, frecuencia y ángulo de zancada y la duración de las diferentes sub-fases del tiempo de contacto se calcularon usando un sistema óptico. Se midió el VO2 para calcular la RE. Los atletas WT fueron más económicos que los RR y presentaron menores tc, mayores tsw, zancadas más largas, frecuencias más bajas y ángulos mayores (P<0.05). Además, los atletas WT experimentaron la sub-fase propulsiva más tarde que los RR (P<0.05). La RE estuvo positivamente relacionada con el tc, la frecuencia de zancada y el ritmo de 10 km, mientras que estuvo negativamente relacionada con el tsw, longitud y ángulo de zancada y la sub-fase propulsiva. Estos resultados sugieren que una biomecánica caracterizada por zancadas más largas, ángulos de zancada y tsw mayores, menores frecuencias y tc, y sub-fases propulsivas más tardías pueden favorecer un uso energético más eficiente.</p

Modelling chemistry in the nocturnal boundary layer above tropical rainforest and a generalised effective nocturnal ozone deposition velocity for sub-ppbv NOx conditions

Measurements of atmospheric composition have been made over a remote rainforest landscape. A box model has previously been demonstrated to model the observed daytime chemistry well. However the box model is unable to explain the nocturnal measurements of relatively high [NO] and [O3], but relatively low observed [NO2]. It is shown that a one-dimensional (1-D) column model with simple O3 -NOx chemistry and a simple representation of vertical transport is able to explain the observed nocturnal concentrations and predict the likely vertical profiles of these species in the nocturnal boundary layer (NBL). Concentrations of tracers carried over from the end of the night can affect the atmospheric chemistry of the following day. To ascertain the anomaly introduced by using the box model to represent the NBL, vertically-averaged NBL concentrations at the end of the night are compared between the 1-D model and the box model. It is found that, under low to medium [NOx] conditions (NOx <1 ppbv), a simple parametrisation can be used to modify the box model deposition velocity of ozone, in order to achieve good agreement between the box and 1-D models for these end-of-night concentrations of NOx and O3. This parametrisation would could also be used in global climate-chemistry models with limited vertical resolution near the surface. Box-model results for the following day differ significantly if this effective nocturnal deposition velocity for ozone is implemented; for instance, there is a 9% increase in the following day’s peak ozone concentration. However under medium to high [NOx] conditions (NOx > 1 ppbv), the effect on the chemistry due to the vertical distribution of the species means no box model can adequately represent chemistry in the NBL without modifying reaction rate constants

An Aeroacoustic Study of Airfoil Self-Noise for Wind Turbine Applications

The current study addresses the issue of noise relating to both large and small scale wind turbines. In utility scale applications, larger size rotors in new generations of wind turbines bring an increasing challenge to manage noise emissions. A better understanding of wind turbine noise characteristics, behaviour and generation mechanics can facilitate the development of noise reduction strategies. This can greatly aid in their adoption. The issue of noise, however, is not exclusive to large scale wind turbines. Small scale wind turbines, operating in laminar or transitional regimes, has the potential to emit tonal noise which can be more audible and of a greater nuisance. Small scale wind turbines can be installed in higher traffic areas closer to human receptors. As such, the understanding of their noise characteristics, behaviour and generation mechanics is important as well. In Reynolds number regime where small scale wind turbine operates, tonal noise is primarily caused by laminar boundary layer-vortex shedding (LBL-VS) noise generation mechanism. In the controlled environment of a closed circuit wind tunnel, the SD-7037 airfoil profile is examined at Re = 4.0 x 10^4. Acoustic measurements are collected when the airfoil is under dynamic oscillation and under various static angles of attack. Results found evidence to suggest LBL-VS noise originated from the suction side of the airfoil in this study; suggesting noise reduction efforts should be focused on suction side phenomenon in similar low Reynold number flow (Re < 10^5). Under dynamic oscillation, airfoil self-noise is studied in condition more representative of outdoor conditions. The tonal noise was found to be reduced compared with static low angles of attack results. The tones were also seen as intermittent; appearing at certain phases of the oscillation cycle. Side peaks were also found at the narrowband acoustic spectra; with the cause linked to the dynamic oscillating frequency. Trailing edge saw-tooth serrations, which have been used on large scale wind turbines, are examined for their noise reduction properties with the SD-7037 airfoil profile. The results were found to be mixed. For larger scale wind turbines, turbulent boundary layer flow more commonly found on the surface of the airfoil, leading to the generation of broadband noise at the trailing edge. The current study examines a 10 m diameter passive controlled wind turbine at the Wind Energy Group outdoor wind turbine test site. The behaviour of the wind turbine noise with respect to on site parameters such as upstream wind speed, upstream wind direction, wind turbine yaw direction, wind turbine blade pitch angle and wind turbine rotor rpm are examined. The feasibility for performing further acoustic experiments at the Wind Energy Group outdoor wind turbine test site is also assessed