We investigated experimentally the settling behaviour of vertically aligned spherical particles within various quiescent media at different release frequencies. The particles had a diameter of $d = 4$ mm and density of $\rho _s = 2200$ kg m$^{-3}$, and were released near the free surface of water, ethanol, a G60 water–glycerine mixture (60 % glycerine by weight) and oil media at frequencies of $f_P = 4$, 6 and 8 Hz, thereby allowing study of Galileo numbers, $Ga \in [16, 976]$. Particle tracking velocimetry quantified the motion of nearly 800 particles in a 600 mm high tank, and particle image velocimetry examined flow patterns around the particles. Results revealed that the centre of mass of the particle trajectories exhibited preferential in-plane motions, with significant lateral dispersion and large $Ga$ in water and ethanol, and nearly vertical paths with low $Ga$ in the G60 mixture and oil media. Varying degrees of particle separation resulted in higher terminal velocities than for a single particle. Hence, particle drag decreased in all cases, with the oil medium showing the highest drag reduction under the closest particle separation, reaching up to nearly 70 % of that for the single particle. The vertical and lateral pair dispersions, $R^2_z$ and $R^2_L$, exhibited ballistic scaling, with dependences on the initial separation, $r_0$, and the type of medium. With large $Ga$, $R^2_z$ displayed a ballistic regime followed by a slower rate, whereas with small $Ga$, $R^2_z$ maintained a consistent ballistic regime throughout settling. Finally, normalized $R^2_z$ demonstrated distinct scaling (exponent 2/3 and 1) dependent on the normalized initial separation and $Ga$.

The aims of this study were to examine the spillover effects of violent attacks, coronavirus disease-2019 (COVID-19) exposure, and their interactions on health professionals’ mental health, and the role of organizational support in their relationships in China. A two-phase survey data (n = 10,901) before and after the first outbreak of COVID-19 was integrated with regional macro data on the number of lawsuit cases of violent attacks and COVID-19 cases. Three studies were designed to isolate the general spillover impact of violent attacks on the mental health of health professionals, how COVID-19 affects the mental health of health professionals, and whether organizational support moderates the relationship between violent attacks and mental health through econometric regressions. Violent attacks and COVID-19 are negatively associated with the mental health of health professionals, and the outbreak of COVID-19 adversely deteriorates the spillover effects of violent attacks. Physicians, not nurses, are the most affected group. Better perceived support from hospitals can significantly mitigate the adverse effects of COVID-19, violent attacks, and their interactions on the mental health of health professionals. COVID-19 deteriorates the adverse effects of violent attacks on the mental health of health professionals, while better organizational support is helpful to mitigate these effects.

REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a redesigned user interface. We also make a major update of the underlying estimation method with penalized beta regression, which demonstrates great reliability and accuracy in dose estimation and uncertainty quantification. In this note, we describe the method and implementation of REAP-2 with a highlight on potency estimation and drug comparison.

A set of vertices in a graph is a Hamiltonian subset if it induces a subgraph containing a Hamiltonian cycle. Kim, Liu, Sharifzadeh, and Staden proved that for large $d$, among all graphs with minimum degree $d$, $K_{d+1}$ minimises the number of Hamiltonian subsets. We prove a near optimal lower bound that takes also the order and the structure of a graph into account. For many natural graph classes, it provides a much better bound than the extremal one ($\approx 2^{d+1}$). Among others, our bound implies that an $n$-vertex $C_4$-free graph with minimum degree $d$ contains at least $n2^{d^{2-o(1)}}$ Hamiltonian subsets.

Rodents and shrews are major reservoirs of various pathogens that are related to zoonotic infectious diseases. The purpose of this study was to investigate co-infections of zoonotic pathogens in rodents and shrews trapped in four provinces of China. We sampled different rodent and shrew communities within and around human settlements in four provinces of China and characterised several important zoonotic viral, bacterial, and parasitic pathogens by PCR methods and phylogenetic analysis. A total of 864 rodents and shrews belonging to 24 and 13 species from RODENTIA and EULIPOTYPHLA orders were captured, respectively. For viral pathogens, two species of hantavirus (Hantaan orthohantavirus and Caobang orthohantavirus) were identified in 3.47% of rodents and shrews. The overall prevalence of Bartonella spp., Anaplasmataceae, Babesia spp., Leptospira spp., Spotted fever group Rickettsiae, Borrelia spp., and Coxiella burnetii were 31.25%, 8.91%, 4.17%, 3.94%, 3.59%, 3.47%, and 0.58%, respectively. Furthermore, the highest co-infection status of three pathogens was observed among Bartonella spp., Leptospira spp., and Anaplasmataceae with a co-infection rate of 0.46%. Our results suggested that species distribution and co-infections of zoonotic pathogens were prevalent in rodents and shrews, highlighting the necessity of active surveillance for zoonotic pathogens in wild mammals in wider regions.

Continuous risky decisions refer to decisions that involve trade-offs among options with persistent risks. People can use the probability of occurrence per unit time (e.g., ‘the probability of occurrence is 1% per month’) or the average time of risk occurrence (e.g., ‘the average occurrence time is 100 months’) to represent continuous risky options. In this study, we examined the effect of the presentation format (i.e., the probability of occurrence per unit time vs. the average time of risk occurrence) on continuous risky decisions in the gain domain and further explored the underlying mechanism. In Study 1 (N = 122), we demonstrated the effect of presentation format on continuous risky decisions and the moderating effect of the magnitude of probabilities. Specifically, when the probabilities were relatively low, compared with the probability of occurrence per unit time, using the average time of risk occurrence to present the continuous risky options led to more risk-averse decisions. However, when the probabilities were relatively high, compared with the probability of occurrence per unit time, the presentation format of the average time occurrence led to more risk-seeking decisions. In Study 2 (N = 136), we found that the moderating effect of the option probabilities on continuous risky decisions was mediated by the subjective attribute-wise difference judgment. In Study 3 (N = 221), we replicated the effect of presentation format on continuous risky decisions in more natural scenarios. The study offered a deep understanding of the mechanism of continuous risky decision-making, and the results were conducive to further developing theories in relevant fields.