Session 11: \u3cem\u3eCan machine learning predict particle deposition at specific intranasal regions based on computational fluid dynamics inputs/outputs and nasal geometry measurements?\u3c/em\u3e

Along with machine learning modeling, numerical simulations of respiratory airflow and particle transport can be used to improve targeted deposition at the upper respiratory infection site of numerous airborne diseases. Given the need for more patient data from varied demographics, we propose a machine learning-enabled protocol for determining optimal formulation design parameters that may match nasal spray device settings for successful drug delivery. We measured 11 anatomical parameters (including nasopharyngeal volume, nostril heights, and mid-nasal cavity volume) for 10 CT-based nasal geometries representative of the population for this aim. We also ran 160 computational fluid dynamics simulations of drug delivery on the same geometries for various breathing situations, using varied pressure gradients to drive inhaled air transport to evaluate drug deposition at the various upper airway areas for nasal inhalers. Using this test data, we constructed 18 machine-learning models to estimate the targeted deposition at the different regions of the upper airway. This study contributes to developing a customized, efficient intranasal delivery system for prophylactics, treatments, and immunizations; the findings will apply to a broad spectrum of respiratory disorders

pH Dependent C-jejuni Thermal Inactivation Models And Application To Poultry Scalding

Campylobacter jejuni related outbreaks and prevalence on retail poultry products pose threats to public health and cause financial burden worldwide. To resolve these problems, it is imperative to take a closer look at poultry processing practices and standards. Using available data (D-values) on the thermal inactivation of C. jejuni we develop a comprehensive inactivation model, taking into account the variation of strain-specific heat resistance, experimental method, and suspension pH. Utilizing our C. jejuni thermal inactivation model, we study the poultry scalding process. We present a mechanistic model of bacteria transfer and inactivation during a typical immersion scald in a high-speed industrial plant. Integration of our C. jejuni inactivation model into the scalding model culminates in validation against industrial processing data. In particular, we successfully predict bacteria concentrations in the scald water and link key factors such as scald water pH and temperature to cross-contamination and overall microbiological quality of carcasses. Furthermore, we demonstrate the applicability of our inactivation model for scalding operations at seven Canadian poultry plants. In addition to providing recommendations for best-practice and a review of scalding research, our work is intended to act as a modular foundation for further research in the interest of public health and financial well-being. (C) 2017 Elsevier Ltd. All rights reserved

Individual Based Modeling And Analysis Of Pathogen Levels In Poultry Chilling Process

Pathogen control during poultry processing critically depends on more enhanced insight into contamination dynamics. In this study we build an individual based model (IBM) of the chilling process. Quantifying the relationships between typical Canadian processing specifications, water chemistry dynamics and pathogen levels both in the chiller water and on individual carcasses, the IBM is shown to provide a useful tool for risk management as it can inform risk assessment models. We apply the IBM to Campylobacter spp. contamination on broiler carcasses, illustrating how free chlorine (FC) sanitization, organic load in the water, and pre-chill carcass pathogen levels affect pathogen levels of post-chill broilers. In particular, given a uniform distribution of Campylobacter levels on incoming poultry we quantify the efficacy of FC control in not only reducing pathogen levels on average, but also the variation of pathogen levels on poultry exiting the chill tank. Furthermore, we demonstrate that the absence/presence of FC input dramatically influences when, during a continuous chilling operation, cross-contamination will be more likely

Individual Based Modeling And Analysis Of Pathogen Levels In Poultry Chilling Process

Pathogen control during poultry processing critically depends on more enhanced insight into contamination dynamics. In this study we build an individual based model (IBM) of the chilling process. Quantifying the relationships between typical Canadian processing specifications, water chemistry dynamics and pathogen levels both in the chiller water and on individual carcasses, the IBM is shown to provide a useful tool for risk management as it can inform risk assessment models. We apply the IBM to Campylobacter spp. contamination on broiler carcasses, illustrating how free chlorine (FC) sanitization, organic load in the water, and pre-chill carcass pathogen levels affect pathogen levels of post-chill broilers. In particular, given a uniform distribution of Campylobacter levels on incoming poultry we quantify the efficacy of FC control in not only reducing pathogen levels on average, but also the variation of pathogen levels on poultry exiting the chill tank. Furthermore, we demonstrate that the absence/presence of FC input dramatically influences when, during a continuous chilling operation, cross-contamination will be more likely

Tracking the Fine Scale Movements of Fish using Autonomous Maritime Robotics: A Systematic State of the Art Review

This paper provides a systematic state of the art review on tracking the fine scale movements of fish with the use of autonomous maritime robotics. Knowledge of migration patterns and the localization of specific species of fish at a given time is vital to many aspects of conservation. This paper reviews these technologies and provides insight into what systems are being used and why. The review results show that a larger amount of complex systems that use a deep learning techniques are used over more simplistic approaches to the design. Most results found in the study involve Autonomous Underwater Vehicles, which generally require the most complex array of sensors. The results also provide insight into future research such as methods involving swarm intelligence, which has seen an increase in use in recent years. This synthesis of current and future research will be helpful to research teams working to create an autonomous vehicle with intentions to track, navigate or survey

A rotational and vibrational investigation of phenylpropiolonitrile (C6_6H5_5C3_3N)

The evidence for benzonitrile (C$_6$H$_5$CN}) in the starless cloud core TMC-1 makes high-resolution studies of other aromatic nitriles and their ring-chain derivatives especially timely. One such species is phenylpropiolonitrile (3-phenyl-2-propynenitrile, C$_6$H$_5$C$_3$N), whose spectroscopic characterization is reported here for the first time. The low resolution (0.5 cm$^{-1}$) vibrational spectrum of C$_6$H$_5$C$_3$N} has been recorded at far- and mid-infrared wavelengths (50 - 3500 cm$^{-1}$) using a Fourier Transform interferometer, allowing for the assignment of band centers of 14 fundamental vibrational bands. The pure rotational spectrum of the species has been investigated using a chirped-pulse Fourier transform microwave (FTMW) spectrometer (6 - 18 GHz), a cavity enhanced FTMW instrument (6 - 20 GHz), and a millimeter-wave one (75 - 100 GHz, 140 - 214 GHz). Through the assignment of more than 6200 lines, accurate ground state spectroscopic constants (rotational, centrifugal distortion up to octics, and nuclear quadrupole hyperfine constants) have been derived from our measurements, with a plausible prediction of the weaker bands through calculations. Interstellar searches for this highly polar species can now be undertaken with confidence since the astronomically most interesting radio lines have either been measured or can be calculated to very high accuracy below 300 GHz.Comment: 7 figures, 4 tables. Accepted for publication in J. Mol. Spe

LHS6343C: A Transiting Field Brown Dwarf Discovered by the Kepler Mission

We report the discovery of a brown dwarf that transits one member of the M+M binary system LHS6343AB every 12.71 days. The transits were discovered using photometric data from the Kelper public data release. The LHS6343 stellar system was previously identified as a single high-proper-motion M dwarf. We use high-contrast imaging to resolve the system into two low-mass stars with masses 0.45 Msun and 0.36 Msun, respectively, and a projected separation of 55 arcsec. High-resolution spectroscopy shows that the more massive component undergoes Doppler variations consistent with Keplerian motion, with a period equal to the transit period and an amplitude consistent with a companion mass of M_C = 62.8 +/- 2.3 Mjup. Based on an analysis of the Kepler light curve we estimate the radius of the companion to be R_C = 0.832 +/- 0.021 Rjup, which is consistent with theoretical predictions of the radius of a > 1 Gyr brown dwarf.Comment: Our previous analysis neglected the dependence of the scaled semimajor axis, a/R, on the transit depth. By not correcting a/R for the third-light contamination, we overestimated the mass of Star A, which led to an overestimate the mass and radius of the LHS6343

On a model-based approach to improve intranasal spray targeting for respiratory viral infections

The nasopharynx, at the back of the nose, constitutes the dominant initial viral infection trigger zone along the upper respiratory tract. However, as per the standard recommended usage protocol (“Current Use”, or CU) for intranasal sprays, the nozzle should enter the nose almost vertically, resulting in sub-optimal nasopharyngeal drug deposition. Through the Large Eddy Simulation technique, this study has replicated airflow under standard breathing conditions with 15 and 30 L/min inhalation rates, passing through medical scan-based anatomically accurate human airway cavities. The small-scale airflow fluctuations were resolved through use of a sub-grid scale Kinetic Energy Transport Model. Intranasally sprayed droplet trajectories for different spray axis placement and orientation conditions were subsequently tracked via Lagrangian-based inert discrete phase simulations against the ambient inhaled airflow field. Finally, this study verified the computational projections for the upper airway drug deposition trends against representative physical experiments on sprayed delivery performed in a 3D-printed anatomic replica. The model-based exercise has revealed a new “Improved Use” (or, IU) spray usage protocol for viral infections. It entails pointing the spray bottle at a shallower angle (with an almost horizontal placement at the nostril), aiming slightly toward the cheeks. From the conically injected spray droplet simulations, we have summarily derived the following inferences: (a) droplets sized between 7–17 μm are relatively more efficient at directly reaching the nasopharynx via inhaled transport; and (b) with realistic droplet size distributions, as found in current over-the-counter spray products, the targeted drug delivery through the IU protocol outperforms CU by a remarkable 2 orders-of-magnitude

Skunk River Review 2012, vol 24

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