Design and Calibration of a Lightweight Physics-Based Model for Fluid-Mediated Self-Assembly of Robotic Modules

In this paper, we consider a system consisting of multiple floating robotic modules performing self-assembly. Faithfully modeling such a system and its inter-module interactions typically involves capturing the hydrodynamic forces acting on the modules using computationally expensive fluid dynamic modeling tools. This poses restrictions on the usability of the resulting models. Here, we present a new approach towards modeling such systems. First, we show how the hardware and firmware of the robotic modules can be faithfully modeled in a high-fidelity robotic simulator. Second, we develop a physics plugin to recreate the hydrodynamic forces acting on the modules and propose a trajectory-based method for calibrating the plugin model parameters. Our calibration method employs a Particle Swarm Optimization (PSO) algorithm, and consists of minimizing the difference between Mean Squared Displacement (MSD) data extracted from real and simulated trajectories of multiple robotic modules

Knowledge of dental academics about the COVID-19 pandemic: a multi-country online survey

Background: COVID-19 is a global pandemic affecting all aspects of life in all countries. We assessed COVID-19 knowledge and associated factors among dental academics in 26 countries. Methods: We invited dental academics to participate in a cross-sectional, multi-country, online survey from March to April 2020. The survey collected data on knowledge of COVID-19 regarding the mode of transmission, symptoms, diagnosis, treatment, protection, and dental treatment precautions as well as participants’ background variables. Multilevel linear models were used to assess the association between dental academics’ knowledge of COVID-19 and individual level (personal and professional) and country-level (number of COVID-19 cases/ million population) factors accounting for random variation among countries. Results: Two thousand forty-five academics participated in the survey (response rate 14.3%, with 54.7% female and 67% younger than 46 years of age). The mean (SD) knowledge percent score was 73.2 (11.2) %, and the score of knowledge of symptoms was significantly lower than the score of knowledge of diagnostic methods (53.1 and 85.4%, P < 0.0001). Knowledge score was significantly higher among those living with a partner/spouse than among those living alone (regression coefficient (B) = 0.48); higher among those with PhD degrees than among those with Bachelor of Dental Science degrees (B = 0.48); higher among those seeing 21 to 30 patients daily than among those seeing no patients (B = 0.65); and higher among those from countries with a higher number of COVID-19 cases/million population (B = 0.0007). Conclusions: Dental academics had poorer knowledge of COVID-19 symptoms than of COVID-19 diagnostic methods. Living arrangements, academic degrees, patient load, and magnitude of the epidemic in the country were associated with COVD-19 knowledge among dental academics. Training of dental academics on COVID-19 can be designed using these findings to recruit those with the greatest need

Perceived preparedness of dental academic institutions to cope with the COVID-19 pandemic: a multi-country survey

Dental academic institutions are affected by COVID-19. We assessed the perceived COVID19 preparedness of these institutions and the characteristics of institutions with greater perceived preparedness. An international cross-sectional survey of dental academics was conducted from March to August 2020 to assess academics’ and institutional attributes, perceived preparedness, and availability of infection prevention and control (IPC) equipment. Principal component analysis (PCA) identified perceived preparedness components. Multilevel linear regression analysis assessed the association between perceived preparedness and fixed effect factors (academics’ and institutions’ attributes) with countries as random effect variable. Of the 1820 dental academics from 28 countries, 78.4% worked in public institutions and 75.2% reported temporary closure. PCA showed five components: clinic apparel, measures before and after patient care, institutional policies, and availability of IPC equipment. Significantly less perceived preparedness was reported in lower-middle income (LMICs) (B = −1.31, p = 0.006) and upper-middle income (UMICs) (B = −0.98, p = 0.02) countries than in high-income countries (HICs), in teaching only (B = −0.55, p < 0.0001) and in research only (B = −1.22, p = 0.003) than teaching and research institutions and in institutions receiving ≤100 patients daily than those receiving >100 patients (B = −0.38, p < 0.0001). More perceived preparedness was reported by academics with administrative roles (B = 0.59, p < 0.0001). Academics from low-income countries (LICs) and LMICs reported less availability of clinic apparel, IPC equipment, measures before patient care, and institutional policies but more measures during patient care. There was greater perceived preparedness in HICs and institutions with greater involvement in teaching, research, and patient care

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Habitat features and performance interact to determine the outcomes of terrestrial predator-prey pursuits

Animals are responsive to predation risk, often seeking safer habitats at the cost of foraging rewards. Although previous research has examined how habitat features affect detection by predators, little is known about how the interaction of habitat features, sensory cues and physical performance capabilities affect prey escape performance once detected.li>To investigate how specific habitat features affect predation risk, we developed an individual-based model of terrestrial predator–prey pursuits in habitats with programmable features. We ran simulations varying the relative performance capabilities of predator and prey as well as the availability and abundance of refuges and obstacles in the habitat.Prey were more likely to avoid detection in complex habitats containing a higher abundance of obstacles; however, if detected, prey escape probability was dependent on both the abundance of refuges and obstacles and the predator's relative performance capabilities. Our model accurately predicted the relative escape success for impala escaping from cheetah in open savanna versus acacia thicket habitat, though escape success was consistently underestimated.Our model provides a mechanistic explanation for the differential effects of habitat on survival for different predator–prey pairs. Its flexible nature means that our model can be refined to simulate specific systems and could have applications towards management programmes for species threatened by habitat loss and predation