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

Towards an improved understanding of the biomechanical implications and risk of injury of barefoot running

Includes bibliographical references.Barefoot running is a subject of significant interest, both in scientific publications and in the lay media as a result of its alleged benefits for runners. These benefits include the potential to reduce injury risk, more economical running and broadly speaking, a better understanding of running biomechanics. Although there are numerous scientific publications describing differences between barefoot and shod running, there is a dearth in understanding whether all runners are able to adapt to the proposed benefits and how this may affect long-term injury risk. Thus, we sought to investigate the biomechanical, neuromuscular and metabolic changes associated with habitually shod runners during the transition to pure barefoot running over an 8- week progressive training programme. This thesis begins with a critical review of the literature, which evaluates the theories and evidence for barefoot running, as well as describing the necessary future research to confirm or refute the barefoot running hypotheses. Our first study aimed to describe acute changes occurring in habitually shod runners when first exposed to barefoot running. We were particularly interested in the variability in response, and whether we could identify factors that predicted potentially favourable changes in kinematic and kinetic outcomes. Fifty-one runners were recruited and assessed using a 3-D motion capture system and integrated force platforms using conventional methods. We found that loading rate was significantly greater in the barefoot condition, but that high individual variability existed, particularly in the barefoot trials. We found that an increase in ankle dorsiflexion is associated with an increase in initial loading rate when in the barefoot condition, supporting previous findings in this regard. We then performed a supervised, pure barefoot running training programme, over 8 weeks, to determine whether the biomechanics of barefoot running would adapt gradually to habituation. Twenty-three runners were recruited for participation, and performed comprehensive biomechanical and neuromuscular assessments before and after the 8-week programme. The first finding was runners do not adapt similarly to barefoot training, and that biomechanics do not change significantly over the 8-week period. High variability in ankle kinematics and loading rate were found, with three sub-groups identified, namely positive responders (reduced loading rate after training), non-responders (no change in loading rate) and negative responders (increase in loading rate after training). We found significant associations between initial loading rate the changes in ankle flexion angle at initial ground contact, presumably as a result of its influence on footstrike. This finding suggests that conscious instruction might be necessary in order to achieve reductions in collision forces during barefoot running. With respect to neuromuscular variables, a persistently higher gastrocnemii muscle preactivation was found in the barefoot condition before and after the training intervention. Increased gastrocnemius pre-activation was associated with lower initial loading rate. An increase in gluteus medius and peroeus longus and a decrease in tibialis anterior pre-activation were also associated with a reduction in initial loading rate after barefoot training. This finding suggests a refined neuromuscular activation strategy prior to ground contact in the barefoot condition to stabilize the hip and centre of mass. Lastly, oxygen cost of transport was found to improve as a result of the barefoot training programme in the male runners and this improvement was found to be associated with a decrease in ground contact time and increase in stride frequency, but no a change in ankle flexion angle at initial ground contact. The outcomes from this thesis elucidate the highly variable response of individuals to barefoot running. This advises individuals choosing to transition to barefoot running to do so with caution. With this in mind, we suggest certain characteristics that may be used as screening mechanisms to indicate individual suitability to barefoot running based on the “collision force theory”. Further, benefits associated with barefoot running other than varied responses in initial loading rate such as improvements in oxygen cost of running are pre-dominantly hypothesised to be a result of musculo-tendinous adaptations, neuromuscular strength and motor control

The maintenance of Body Fluid Homestasis during exercise when drinking ad Libitum

The prescription of an optimal fluid intake during exercise has been a controversial subject in sports science over the past decade. Only recently has it evolved from 'blanket' prescriptions to more individualised recommendations. Currently the American College of Sports Medicine (ACSM) advise that sufficient fluid should be drunk in order to ensure that body mass (BM) loss does not exceed >2% of starting BM in order to avoid exercise-associated medical complications. Historically BM changes have been used as a surrogate for fluid loss during exercise. It would be helpful to accurately determine fluid shifts in the body in order to provide physiologically appropriate fluid intake advice. The measurement of total body water (TBW) via deuterium oxide has been found to be the most accurate measure to detect changes in body fluid content. Thus the aim of this thesis was to understand body fluid homeostasis during exercise when drinking according to the dictates of thirst (ad libitum). This thesis begins with a review of the literature examining the basis for fluid intake prescription with the use of BM, the concepts of 'voluntary and involuntary dehydration' and the major routes by which the body is potentially able to gain and lose fluid during exercise. We initially found that changes in TBW are more variable than BM at rest, although technical machine error accounted for a majority of the total error in the TBW measurement. Interestingly BM remains very stable at rest compared to the dynamic nature of changes in TBW both daily and weekly. We also found that measurements of both BM and TBW produce reproducible results at rest. Our first finding was that with the adoption of an ad libitum fluid intake during exercise athletes participating in the study were able to finish races of varying distances without any medical complication along with a >2% BM loss. Which leads onto our second and more important finding that we have also demonstrated that despite a >2% BM loss, all of our subjects finished their respective races whilst maintaining plasma sodium concentration ([Na+]) and plasma osmolality (POsm) within the normal range when drinking ad libitum. This finding demonstrates the reality of drinking in athletes competing in various types of foot races and that it is unnecessary to drink to maintain BM in order to successfully complete races of any distance Thirdly and most pertinent finding was that associated with this >2% BM loss we measured TBW changes during these races and found that changes in BM do not track changes in TBW during real-life competition in athletes when drinking ad libitum. This finding illustrates that to some extent, sweat losses during exercise are offset by internal water sources associated with metabolic water formation and water associated with glycogen storage ensuring the maintenance of body fluid homeostasis. It was also noted that athletes performing the best often experience the greatest BM loss during the 21.1km and we found a similar trend in the 56km race. We have suggested that this can be explained by both behavioural and physiological reasons. Lastly all athletes successfully completed their respective races without encountering any exercise-associated medical complications with the adoption of an ad libitum fluid intake approach. The outcomes from this thesis support the prescription of more physiologically appropriate advice for fluid intake prescription during exercise. We hope that these studies will provide adequate corroboration that during exercise together with an ad libitum approach, athletes are able to maintain adequate hydration (maintenance of POsm and plasma [Na+]) regardless of significant decreases in BM, which is often associated with superior performance in some athletes

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

Deep learning on the 2-dimensional Ising model to extract the crossover region with a variational autoencoder

The 2-dimensional Ising model on a square lattice is investigated with a variational autoencoder in the non-vanishing field case for the purpose of extracting the crossover region between the ferromagnetic and paramagnetic phases. The encoded latent variable space is found to provide suitable metrics for tracking the order and disorder in the Ising configurations that extends to the extraction of a crossover region in a way that is consistent with expectations. The extracted results achieve an exceptional prediction for the critical point as well as agreement with previously published results on the configurational magnetizations of the model. The performance of this method provides encouragement for the use of machine learning to extract meaningful structural information from complex physical systems where little a priori data is available

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