Optimization of Pathogen Capture in Flowing Fluids with Magnetic Nanoparticles

Magnetic nanoparticles have been employed to capture pathogens for many biological applications; however, optimal particle sizes have been determined empirically in specific capturing protocols. Here, a theoretical model that simulates capture of bacteria is described and used to calculate bacterial collision frequencies and magnetophoretic properties for a range of particle sizes. The model predicts that particles with a diameter of 460 nm should produce optimal separation of bacteria in buffer flowing at 1 L h⁻¹. Validating the predictive power of the model, Staphylococcus aureus is separated from buffer and blood flowing through magnetic capture devices using six different sizes of magnetic particles. Experimental magnetic separation in buffer conditions confirms that particles with a diameter closest to the predicted optimal particle size provide the most effective capture. Modeling the capturing process in plasma and blood by introducing empirical constants (c_e), which integrate the interfering effects of biological components on the binding kinetics of magnetic beads to bacteria, smaller beads with 50 nm diameters are predicted that exhibit maximum magnetic separation of bacteria from blood and experimentally validated this trend. The predictive power of the model suggests its utility for the future design of magnetic separation for diagnostic and therapeutic applications.     

Burst Detection by Water Demand Nowcasting Based on Exogenous Sensors

Bursts of drinking water pipes not only cause loss of drinking water, but also damage below and above ground infrastructure. Short-term water demand forecasting is a valuable tool in burst detection, as deviations between the forecast and actual water demand may indicate a new burst. Many of burst detection methods struggle with false positives due to non-seasonal water consumption as a result of e.g. environmental, economic or demographic exogenous influences, such as weather, holidays, festivities or pandemics. Finding a robust alternative that reduces the false positive rate of burst detection and does not rely on data from exogenous processes is essential. We present such a burst detection method, based on Bayesian ridge regression and Random Sample Consensus. Our exogenous nowcasting method relies on signals of all nearby flow and pressure sensors in the distribution net with the aim to reduce the false positive rate. The method requires neither data of exogenous processes, nor extensive historical data, but only requires one week of historical data per flow/pressure sensor. The exogenous nowcasting method is compared with a common water demand forecasting method for burst detection and shows sufficiently higher Nash-Sutcliffe model efficiencies of 82.7% - 90.6% compared to 57.9% - 77.7%, respectively. These efficiency ranges indicate a more accurate water demand prediction, resulting in more precise burst detection.

     

The future of irradiation applications on Earth and in space

What needs to be done to establish food irradiation on a truly commercial basis so that those living on planet Earth can fully realize the benefits of this versatile process? This question is answered in the first part of this paper. The second part covers the potential contributions of irradiated foods to feed humans in space.     

Theory of porous electrodes—XI. The positive plate of the lead-acid battery

Partial differential equations describing the transport of mass and electricity in the pores of the positive electrode of a lead acid battery were derived. The theory is based on exact transport equations and on the assumption that the solid porous matrix has a metallic conductivity. Volume changes in both phases are taken into account. Numerical solutions obtained on a computer are presented for the case where the influence of electrolyte between the electrodes can be neglected. The solutions depend on the product of electrode thickness times current density, and on the initial porosity.     

Numerical solutions of unsteady flows with low inlet Mach numbers

This study deals with a numerical solution of a 2D unsteady flow of a compressible viscous fluid in a channel for low inlet airflow velocity. The unsteadiness of the flow is caused by a prescribed periodic motion of a part of the channel wall with large amplitudes, nearly closing the channel during oscillations. The channel is a simplified model of the glottal space in the human vocal tract and the flow can represent a model of airflow coming from the trachea, through the glottal region with periodically vibrating vocal folds, and to the human vocal tract.     

SEBS elastomers for fabrication of microfluidic devices with reduced drug absorption by injection molding and extrusion

The majority of microfluidic devices used for cell culture, including Organ-on-a-Chips (Organ Chips), are fabricated using polydimethylsiloxane (PDMS) polymer because it is flexible, optically clear, and easy to mold. However, PDMS possesses significant challenges for high volume manufacturing and its tendency to absorb small hydrophobic compounds limits its usefulness as a material in devices used for drug evaluation studies. Here, we demonstrate that a subset of optically clear, elastomeric, styrenic block copolymers based on styrene-ethylene-butylene-styrene exhibit reduced absorption of small hydrophobic molecules and drug compounds compared to PDMS and that they can be fabricated into microfluidic devices with fine features and the flexibility required for Organ Chips using mass production techniques of injection molding and extrusion.     

The influence of music on mood and performance while driving

Mood can influence our everyday behaviour and people often seek to reinforce, or to alter their mood, for example by turning on music. Music listening while driving is a popular activity. However, little is known about the impact of music listening while driving on physiological state and driving performance. In the present experiment, it was investigated whether individually selected music can induce mood and maintain moods during a simulated drive. In addition, effects of positive, negative, and no music on driving behaviour and physiological measures were assessed for normal and high cognitive demanding rides. Subjective mood ratings indicated that music successfully maintained mood while driving. Narrow lane width drives increased task demand as shown in effort ratings and increased swerving. Furthermore, respiration rate was lower during music listening compared to rides without music, while no effects of music were found on heart rate. Overall, the current study demonstrates that music listening in car influences the experienced mood while driving, which in turn can impact driving behaviour. PRACTITIONERS SUMMARY: Even though it is a popular activity, little is known about the impact of music while driving on physiological state and performance. We examined whether music can induce moods during high and low simulated drives. The current study demonstrates that in car music listening influences mood which in turn can impact driving behaviour. The current study shows that listening to music can positively impact mood while driving, which can be used to affect state and safe behaviour. Additionally, driving performance in high demand situations is not negatively affected by music.