Raoult's law, published in 1887, is taught in chemistry and chemical engineering fields as a first approximation to the vapor pressure and activity of solutes and solvents in mixtures. In ideal solutions, it is exact but many solutions are known to have substantial deviations from Raoult's law as conventionally interpreted. In 1908, Callendar showed that water hydrated to the solute can explain some of the departures from Raoult's law in aqueous solution. Here, we show that by simply assuming equilibria between the free water in solution and its hydrated forms, Raoult's law and Callendar's extension are valid over the full range of concentrations, while also showing how water and solutes interact in solution. This model of solutions has importance in highly concentrated solutions common in atmosphere aerosols relevant to climate change and air quality, and in numerous industrial processes.

Neonatal and postnatal exposures to air pollutants have adverse effects on lung development resulting in airway structure changes. Usually, generation-averaged analysis of airway geometric parameters is employed to differentiate between pulmonary airway trees. However, this method is limited, especially for monopodial branching trees such as in rat airways, because both quite proximal and less proximal airways that have very different structure and function may be in the same generation. To avoid limitations inherent in generation averaging, we developed a method that compares two trees airway-by-airway using micro CT image data from rat lungs. This computerized technique (1) identifies the geometry and architecture of the conducting airways from CT images, (2) extracts the main tree, (3) associates paired airways from the two different trees, and (4) develops summary statistics on the degree of similarity between populations of animals. By comparing the trees airway-by-airway, we found that the variance in airway length of the group exposed to diffusion flame particles (DFP) is significantly larger than the group raised in filtered air (FA). This method also found that rotation angle of the DFP group is significantly larger than FA, which is not as certain in the generation-based analysis. We suggest that airway-by-airway analysis complements generation-based averaging for detecting airway alterations.

The United States Environmental Protection Agency (US EPA) list of hazardous air pollutants (HAPs) includes toxic metal suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metals in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost-effective technique that can be used for analyzing toxic metals in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metals targeted by the US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. The least absolute shrinkage and selection operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metals from the observed spectra. The limits of detections (LODs) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however, for some toxic metals the single-feature LOD marginally outperforms LASSO LOD. The combination of low-cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data-driven solutions to costly measurements.

Mammalian lungs are comprised of large numbers of tracheobronchial airways that transition from the trachea to alveoli. Studies as wide ranging as pollutant deposition and lung development rely on accurate characterization of these airways. Advancements in CT imaging and the value of computational approaches in eliminating the burden of manual measurement are providing increased efficiency in obtaining this geometric data. In this study, we compare an automated method to a manual one for the first six generations of three Balb/c mouse lungs. We find good agreement between manual and automated methods and that much of the disagreement can be attributed to method precision. Using the automated method, we then provide anatomical data for the entire tracheobronchial airway tree from three Balb/C mice. Anat Rec, 2017. © 2017 Wiley Periodicals, Inc. Anat Rec, 300:2046-2057, 2017. © 2017 Wiley Periodicals, Inc.

In 2019, Wexler showed that, by applying Raoult's law rigorously to aqueous solutions and properly accounting for hydration of solutes, equations can be derived that accurately describe solute and solvent activity over the full range of concentrations from infinitely dilute to pure solutes. One feature of this theory is that it also predicts the amount of water that is free and the amount that is bound to the solute. In 2004 and 2005, Choi and co-workers used an electrodynamic balance to measure (i) the concentration of a range of organic and electrolyte solutes as a function of water activity and (ii) the amount of free and bound water in these solutions using the fluorescence of pyranine as a probe. In the current work, we compare the predictions of Wexler's theory to the measurements of Choi. After the adjustments to the amount of free water obtained by these measurements, the predictions of Wexler's theory match the measurements of Choi. The potential reasons for the adjustments are discussed.

We have recently developed a low-cost spark-induced breakdown spectroscopy (SIBS) instrument for in-situ analysis of toxic metal aerosol particles that we call TARTA (toxic-metal aerosol real time analyzer). In this work, we applied machine learning methods to improve the quantitative analysis of elemental mass concentrations measured by this instrument. Specifically, we applied least absolute shrinkage and selection operator (LASSO), partial least squares (PLS) regression, principal component regression (PCR), and support vector regression (SVR) to develop multivariate calibration models for 13 metals (e.g., Cr, Cu, Mn, Fe, Zn, Co, Al, K, Be, Hg, Cd, Pb, and Ni), some of which are included on the US EPA hazardous air pollutants (HAPS) list. The calibration performance, adjusted coefficient of determination (R²) and normalized root mean square error (RMSE), and limit of detection (LOD) of the proposed models were compared to those of univariate calibration models for each analyte. Our results suggest that machine learning models tend to have better prediction accuracy and lower LODs than conventional univariate calibration, of which the LASSO approach performs the best with R² > 0.8 and LODs of 40-170 ng m^-3 at a sampling time of 30 min and a flow rate of 15 l min ^-1. We then assessed the applicability of the LASSO model for quantifying elemental concentrations in mixtures of these metals, serving as independent validation datasets. Ultimately, the LASSO model developed in this work is a very promising machine learning approach for quantifying mass concentration of metals in aerosol particles using TARTA.

Background

Direct electrical activation of skeletal muscles of patients with upper motor neuron lesions can restore functional movements, such as standing or walking. Because responses to electrical stimulation are highly nonlinear and time varying, accurate control of muscles to produce functional movements is very difficult. Accurate and predictive mathematical models can facilitate the design of stimulation patterns and control strategies that will produce the desired force and motion. In the present study, we build upon our previous isometric model to capture the effects of constant angular velocity on the forces produced during electrically elicited concentric contractions of healthy human quadriceps femoris muscle. Modelling the isovelocity condition is important because it will enable us to understand how our model behaves under the relatively simple condition of constant velocity and will enable us to better understand the interactions of muscle length, limb velocity, and stimulation pattern on the force produced by the muscle.

Methods

An additional term was introduced into our previous isometric model to predict the force responses during constant velocity limb motion. Ten healthy subjects were recruited for the study. Using a KinCom dynamometer, isometric and isovelocity force data were collected from the human quadriceps femoris muscle in response to a wide range of stimulation frequencies and patterns. % error, linear regression trend lines, and paired t-tests were used to test how well the model predicted the experimental forces. In addition, sensitivity analysis was performed using Fourier Amplitude Sensitivity Test to obtain a measure of the sensitivity of our model's output to changes in model parameters.

Results

Percentage RMS errors between modelled and experimental forces determined for each subject at each stimulation pattern and velocity showed that the errors were in general less than 20%. The coefficients of determination between the measured and predicted forces show that the model accounted for approximately 86% and approximately 85% of the variances in the measured force-time integrals and peak forces, respectively.

Conclusion

The range of predictive abilities of the isovelocity model in response to changes in muscle length, velocity, and stimulation frequency for each individual make it ideal for dynamic applications like FES cycling.

Turbulent dispersion of passive scalar quantities has been extensively studied in wind tunnel settings, where the flow is carefully conditioned using flow straighteners and grids. Much less is known about turbulent dispersion in the "unconditioned" flows generated by fans that are ubiquitous in indoor environments, despite the importance of these flows to pathogen and contaminant transport. Here, we demonstrate that a point source of scalars released into an airflow generated by an axial fan yields a plume whose width is invariant with respect to the fan speed. The results point toward a useful simplification in modeling of disease and pollution spread via fan-generated flows.

Abstract Background Our previous model of the non-isometric muscle fatigue that occurs during repetitive functional electrical stimulation included models of force, motion, and fatigue and accounted for applied load but not stimulation pulse duration. Our objectives were to: 1) further develop, 2) validate, and 3) present outcome measures for a non-isometric fatigue model that can predict the effect of a range of pulse durations on muscle fatigue. Methods A computer-controlled stimulator sent electrical pulses to electrodes on the thighs of 25 able-bodied human subjects. Isometric and non-isometric non-fatiguing and fatiguing knee torques and/or angles were measured. Pulse duration (170–600 μs) was the independent variable. Measurements were divided into parameter identification and model validation subsets. Results The fatigue model was simplified by removing two of three non-isometric parameters. The third remained a function of other model parameters. Between 66% and 77% of the variability in the angle measurements was explained by the new model. Conclusion Muscle fatigue in response to different stimulation pulse durations can be predicted during non-isometric repetitive contractions.