The Laboratory Characterization of Fugitive Aerosol Emissions From a Standard Jet Nebulizer With and Without a Filtered Mouthpiece.

Background and objective The risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission from patients with coronavirus disease 2019 (COVID-19) during nebulization is unclear. In this study, we aimed to address this issue. Methods Fugitive emissions of aerosolized saline during nebulization were observed using a standard jet nebulizer fitted with unfiltered and filtered mouthpieces connected via a mannequin to a breathing simulator. Fugitive emissions were observed by using a laser sheet and captured on high-definition video, and they were measured by using optical particle counters positioned where a potential caregiver may be administering nebulization and three other locations in the sagittal plane at various distances downstream of the mannequin. Results The use of a standard unfiltered mouthpiece resulted in significant emission of fugitive aerosols ahead of and above the mannequin (spread over 2 m in front). A mouthpiece with a filter-adaptor effectively suppressed the emissions, with only minor leakage from the nebulizer cup. Particle count measurements supported the visual observations, providing total particle count levels and aerosol concentration levels at the measurement locations. The levels decayed slowly with downstream distance. Conclusions The visualization described above captured the dispersion of emitted aerosols in the plane of the laser sheet, aligned with the sagittal plane. The particle count measurements provided temporal and spatial distributions of the aerosol concentration levels over the time and locations considered. However, the exhaled air and aerosolized droplets spread three-dimensionally in front of and above the mannequin. The results visually highlight the effectiveness of using a filtered mouthpiece in suppressing the fugitive aerosols and identify an approach for limiting the occupational exposure of healthcare workers to these emissions while administering nebulized therapies.

Aerosol generation in public restrooms.

Aerosolized droplets play a central role in the transmission of various infectious diseases, including Legionnaire's disease, gastroenteritis-causing norovirus, and most recently COVID-19. Respiratory droplets are known to be the most prominent source of transmission for COVID-19; however, alternative routes may exist given the discovery of small numbers of viable viruses in urine and stool samples. Flushing biomatter can lead to the aerosolization of micro-organisms; thus, there is a likelihood that bioaerosols generated in public restrooms may pose a concern for the transmission of COVID-19, especially since these areas are relatively confined, experience heavy foot traffic, and may suffer from inadequate ventilation. To quantify the extent of aerosolization, we measure the size and number of droplets generated by flushing toilets and urinals in a public restroom. The results indicate that the particular designs tested in the study generate a large number of droplets in the size range 0.3 µ m - 3 µ m , which can reach heights of at least 1.52 m. Covering the toilet reduced aerosol levels but did not eliminate them completely, suggesting that aerosolized droplets escaped through small gaps between the cover and the seat. In addition to consistent increases in aerosol levels immediately after flushing, there was a notable rise in ambient aerosol levels due to the accumulation of droplets from multiple flushes conducted during the tests. This highlights the need for incorporating adequate ventilation in the design and operation of public spaces, which can help prevent aerosol accumulation in high occupancy areas and mitigate the risk of airborne disease transmission.

Burst-and-coast swimming is not always energetically beneficial in fish (Hemigrammus bleheri).

Burst-and-coast swimming is an intermittent mode of locomotion used by various fish species. The intermittent gait has been associated with certain advantages such as stabilizing the visual field, improved sensing ability, and reduced energy expenditure. We investigate burst-coast swimming in rummy nose tetra fish (Hemigrammus bleheri) using a combination of experimental data and numerical simulations. The experiments were performed in a shallow water channel where the tetra fish swam against an imposed inflow. High speed video recordings of the fish were digitized to extract the undulatory kinematics at various swimming speeds. The kinematics data were then used in Navier-Stokes simulations to prescribe the undulatory motion for three-dimensional geometrical models of the fish. The resulting steady-state speeds of the simulated self-propelled swimmers agree well with the speeds observed experimentally. We examine the power requirements for various realistic swimming modes, which indicate that it is possible to use continuous swimming gaits that require considerably less mechanical energy than intermittent burst-coast modes at comparable speeds. The higher energetic cost of burst-coast swimming suggests that the primary purpose of intermittent swimming may not be to conserve energy, but it may instead be related to a combination of other functional aspects such as improved sensing and the likely existence of a minimum tail-beat frequency. Importantly, using sinusoidal traveling waves to generate intermittent and continuous kinematics, instead of using experiment-based kinematics, results in comparable power requirements for the two swimming modes.

Visualizing droplet dispersal for face shields and masks with exhalation valves.

Several places across the world are experiencing a steep surge in COVID-19 infections. Face masks have become increasingly accepted as one of the most effective means for combating the spread of the disease when used in combination with social-distancing and frequent hand-washing. However, there is an increasing trend of people substituting regular cloth or surgical masks with clear plastic face shields and with masks equipped with exhalation valves. One of the factors driving this increased adoption is improved comfort compared to regular masks. However, there is a possibility that widespread public use of these alternatives to regular masks could have an adverse effect on mitigation efforts. To help increase public awareness regarding the effectiveness of these alternative options, we use qualitative visualizations to examine the performance of face shields and exhalation valves in impeding the spread of aerosol-sized droplets. The visualizations indicate that although face shields block the initial forward motion of the jet, the expelled droplets can move around the visor with relative ease and spread out over a large area depending on light ambient disturbances. Visualizations for a mask equipped with an exhalation port indicate that a large number of droplets pass through the exhale valve unfiltered, which significantly reduces its effectiveness as a means of source control. Our observations suggest that to minimize the community spread of COVID-19, it may be preferable to use high quality cloth or surgical masks that are of a plain design, instead of face shields and masks equipped with exhale valves.

Visualizing the effectiveness of face masks in obstructing respiratory jets.

The use of face masks in public settings has been widely recommended by public health officials during the current COVID-19 pandemic. The masks help mitigate the risk of cross-infection via respiratory droplets; however, there are no specific guidelines on mask materials and designs that are most effective in minimizing droplet dispersal. While there have been prior studies on the performance of medical-grade masks, there are insufficient data on cloth-based coverings, which are being used by a vast majority of the general public. We use qualitative visualizations of emulated coughs and sneezes to examine how material- and design-choices impact the extent to which droplet-laden respiratory jets are blocked. Loosely folded face masks and bandana-style coverings provide minimal stopping-capability for the smallest aerosolized respiratory droplets. Well-fitted homemade masks with multiple layers of quilting fabric, and off-the-shelf cone style masks, proved to be the most effective in reducing droplet dispersal. These masks were able to curtail the speed and range of the respiratory jets significantly, albeit with some leakage through the mask material and from small gaps along the edges. Importantly, uncovered emulated coughs were able to travel notably farther than the currently recommended 6-ft distancing guideline. We outline the procedure for setting up simple visualization experiments using easily available materials, which may help healthcare professionals, medical researchers, and manufacturers in assessing the effectiveness of face masks and other personal protective equipment qualitatively.

Restoring chaos using deep reinforcement learning.

A catastrophic bifurcation in non-linear dynamical systems, called crisis, often leads to their convergence to an undesirable non-chaotic state after some initial chaotic transients. Preventing such behavior has been quite challenging. We demonstrate that deep Reinforcement Learning (RL) is able to restore chaos in a transiently chaotic regime of the Lorenz system of equations. Without requiring any a priori knowledge of the underlying dynamics of the governing equations, the RL agent discovers an effective strategy for perturbing the parameters of the Lorenz system such that the chaotic trajectory is sustained. We analyze the agent's autonomous control-decisions and identify and implement a simple control-law that successfully restores chaos in the Lorenz system. Our results demonstrate the utility of using deep RL for controlling the occurrence of catastrophes in non-linear dynamical systems.

Optimal Flow Sensing for Schooling Swimmers.

Fish schooling implies an awareness of the swimmers for their companions. In flow mediated environments, in addition to visual cues, pressure and shear sensors on the fish body are critical for providing quantitative information that assists the quantification of proximity to other fish. Here we examine the distribution of sensors on the surface of an artificial swimmer so that it can optimally identify a leading group of swimmers. We employ Bayesian experimental design coupled with numerical simulations of the two-dimensional Navier Stokes equations for multiple self-propelled swimmers. The follower tracks the school using information from its own surface pressure and shear stress. We demonstrate that the optimal sensor distribution of the follower is qualitatively similar to the distribution of neuromasts on fish. Our results show that it is possible to identify accurately the center of mass and the number of the leading swimmers using surface only information.

Relative performance of different data mining techniques for nitrate concentration and load estimation in different type of watersheds.

The increasing availability of water quality datasets has led to a greater focus on hydrologic and water quality analysis, thus requiring more efficient and accurate modelling methods. Data mining techniques have been increasingly used for water quality analysis and prediction of the concentration and load of nitrogen pollutants instead of more traditional simulation methods. In this study, we tested the multilayer perceptron (MLP), k-nearest neighbor (k-NN), random forest, and reduced error pruning tree (REPTree) methods, along with the traditional linear regression, to predict nitrate levels based on long-term data from six watersheds with different land-use practices in the midwestern United States. Both the concentration and load results indicated that REPTree had the best performance, with an R2 of 0.61-0.85 and a relative absolute error of <75.8%. The different watershed types, however, influenced the performance of the data mining methods, where all four methods showed a higher accuracy for urban dominant watershed and lower accuracy for agricultural and forest watersheds. Out of these four methods, classification tree methods (REPTree and RF) performed better than cluster methods (MLP and k-NN) for agricultural and forested watersheds. Our results indicated that both the data structure based on the dominant land use and type of algorithmic method should be carefully considered for selecting a data mining method to predict nitrate concentration and load for a watershed.

Efficient collective swimming by harnessing vortices through deep reinforcement learning.

Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm. The RL algorithm relies on a policy defined by deep, recurrent neural nets, with long-short-term memory cells, that are essential for capturing the unsteadiness of the two-way interactions between the fish and the vortical flow field. Surprisingly, we find that swimming in-line with a leader is not associated with energetic benefits for the follower. Instead, "smart swimmer(s)" place themselves at off-center positions, with respect to the axis of the leader(s) and deform their body to synchronize with the momentum of the oncoming vortices, thus enhancing their swimming efficiency at no cost to the leader(s). The results confirm that fish may harvest energy deposited in vortices and support the conjecture that swimming in formation is energetically advantageous. Moreover, this study demonstrates that deep RL can produce navigation algorithms for complex unsteady and vortical flow fields, with promising implications for energy savings in autonomous robotic swarms.

Synchronisation through learning for two self-propelled swimmers.

The coordinated motion by multiple swimmers is a fundamental component in fish schooling. The flow field induced by the motion of each self-propelled swimmer implies non-linear hydrodynamic interactions among the members of a group. How do swimmers compensate for such hydrodynamic interactions in coordinated patterns? We provide an answer to this riddle though simulations of two, self-propelled, fish-like bodies that employ a learning algorithm to synchronise their swimming patterns. We distinguish between learned motion patterns and the commonly used a-priori specified movements, that are imposed on the swimmers without feedback from their hydrodynamic interactions. First, we demonstrate that two rigid bodies executing pre-specified motions, with an alternating leader and follower, can result in substantial drag-reduction and intermittent thrust generation. In turn, we study two self-propelled swimmers arranged in a leader-follower configuration, with a-priori specified body-deformations. These two self-propelled swimmers do not sustain their tandem configuration. The follower experiences either an increase or decrease in swimming speed, depending on the initial conditions, while the swimming of the leader remains largely unaffected. This indicates that a-priori specified patterns are not sufficient to sustain synchronised swimming. We then examine a tandem of swimmers where the leader has a steady gait and the follower learns to synchronize its motion, to overcome the forces induced by the leader's vortex wake. The follower employs reinforcement learning to adapt its swimming-kinematics so as to minimize its lateral deviations from the leader's path. Swimming in such a sustained synchronised tandem yields up to [Formula: see text] reduction in energy expenditure for the follower, in addition to a [Formula: see text] increase in its swimming-efficiency. The present results show that two self-propelled swimmers can be synchronised by adapting their motion patterns to compensate for flow-structure interactions. Moreover, swimmers can exploit the vortical structures of their flow field so that synchronised swimming is energetically beneficial.

Subfilter scalar-flux vector orientation in homogeneous isotropic turbulence.

The geometric orientation of the subfilter-scale scalar-flux vector is examined in homogeneous isotropic turbulence. Vector orientation is determined using the eigenframe of the resolved strain-rate tensor. The Schmidt number is kept sufficiently large so as to leave the velocity field, and hence the strain-rate tensor, unaltered by filtering in the viscous-convective subrange. Strong preferential alignment is observed for the case of Gaussian and box filters, whereas the sharp-spectral filter leads to close to a random orientation. The orientation angle obtained with the Gaussian and box filters is largely independent of the filter width and the Schmidt number. It is shown that the alignment direction observed numerically using these two filters is predicted very well by the tensor-diffusivity model. Moreover, preferred alignment of the scalar gradient vector in the eigenframe is shown to mitigate any probable issues of negative diffusivity in the tensor-diffusivity model. Consequentially, the model might not suffer from solution instability when used for large eddy simulations of scalar transport in homogeneous isotropic turbulence. Further a priori tests indicate poor alignment of the Smagorinsky and stretched vortex model predictions with the exact subfilter flux. Finally, strong filter dependence of subfilter scalar-flux orientation suggests that explicit filtering may be preferable to implicit filtering in large eddy simulations.

Anorectal Leiomyoma : Case Report of Rare Tumor with unusual Presentation.

Gastrointestinal stromal tumour (GIST) is a rare tumour of gastrointestinal tract, comprising of 0.1-3.0% of all gastrointestinal malignancies. They are commonly found in stomach (60-70%), very rarely in rectum and anal canal (<5%). The present case report is of a large anorectal leiomyoma (142×80mm) arising from posterior rectal wall, with its unusual presentation of urinary retention. In our case, in view of its massive size, recurrence and malignant transformation, we planned abdominoperineal resection. Although size and histological grade play an important role, complete resection still is considered the most significant favorable prognostic factor.