Lacking protection compared to drivers of other vehicles, motorcyclists accounted for most casualties and fatalities. This study explores how non-motorcycle drivers affect motorcyclists’ injury outcomes in motorcycle-vehicle collisions. The motorcycle-vehicle crashes from the United Kingdom for 2016–2020 are used to estimate two alternative logit models to account for possible unobserved heterogeneities. The models are a latent class multinomial logit with class probability functions and a random threshold-parameter generalized ordered logit. With three possible injury severity levels (fatal injury, severe injury, and minor injury), the characteristics of motorcyclist, driver, roadway, environment, vehicle, and collision are considered potential determinants. Then, the temporal instability issues are revealed through the likelihood ratio tests and out-of-sample predictions based on the two models. Showing good (Formula presented.) values of over 0.370, the latent class model’s estimation results are leveraged to quantify the effects of the contributing factors. Moreover, the marginal effects are also calculated to reveal the existing temporal instability, while some variables reflect the temporal instability in the influence trend and degree. The critical factors increasing the risk levels are male motorcyclists, higher speed limit, older ages of motorcyclists and vehicles, fine weather, single carriageway, and head-on collision type. Overall, subtle variations in the injury severity predictions exist in alternative heterogeneity modeling approaches, suffering from the modeling mechanism of different structural frameworks in capturing the unobserved heterogeneities.

The transition of bacteria from an individualistic to a biofilm lifestyle profoundly alters their biology. During biofilm development, the bacterial cell-cell adhesions are a major determinant of initial microcolonies, which serve as kernels for the subsequent microscopic and mesoscopic structure of the biofilm, and determine the resulting functionality. In this study, the significance of bacterial cell-cell adhesion dynamics on bacterial aggregation and biofilm maturation is elucidated. Using photoswitchable adhesins between bacteria, modifying the dynamics of bacterial cell-cell adhesions with periodic dark-light cycles is systematic. Dynamic cell-cell adhesions with liquid-like behavior improve bacterial aggregation and produce more compact microcolonies than static adhesions with solid-like behavior in both experiments and individual-based simulations. Consequently, dynamic cell-cell adhesions give rise to earlier quorum sensing activation, better intermixing of different bacterial populations, improved biofilm maturation, changes in the growth of cocultures, and higher yields in fermentation. The here presented approach of tuning bacterial cell-cell adhesion dynamics opens the door for regulating the structure and function of biofilms and cocultures with potential biotechnological applications.