The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections.

Background: The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI.

Role of vibrations in the jamming and unjamming of grains discharging from a silo.

We present experimental results of the jamming of noncohesive particles discharged from a flat bottomed silo subjected to vertical vibration. When the exit orifice is only a few grain diameters wide, the flow can be arrested due to the formation of blocking arches. Hence, an external excitation is needed to resume the flow.