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We combined survey, mobility, and infections data in greater Boston, MA to simulate the effects of racial disparities in the inclination to become vaccinated on continued infection rates and the attainment of herd immunity. The simulation projected marked inequities, with communities of color experiencing infection rates 3 times higher than predominantly White communities and reaching herd immunity 45 days later on average. Persuasion of individuals uncertain about vaccination was crucial to preventing the worst inequities but could only narrow them so far because 1/5th of Black and Latinx individuals said that they would never vaccinate. The results point to a need for well-crafted, compassionate messaging that reaches out to those most resistant to the vaccine.

 

Firefighters are often exposed to extensive wayfinding information in various formats owing to the increasing complexity of the built environment. Because of the individual differences in processing assorted types of information, a personalized cognition-driven intelligent system is necessary to reduce the cognitive load and improve the performance in the wayfinding tasks. However, the mixed and multi-dimensional information during the wayfinding tasks bring severe challenges to intelligent systems in detecting and nowcasting the attention of users. In this research, a virtual wayfinding experiment is designed to simulate the human response when subjects are memorizing or recalling different wayfinding information. Convolutional neural networks (CNNs) are designed for automated attention detection based on the power spectrum density of electroencephalography (EEG) data collected during the experiment. The performance of the personalized model and the generalized model are compared and the result shows a personalized CNN is a powerful classifier in detecting the attention of users with high accuracy and efficiency. The study thus will serve a foundation to support the future development of personalized cognition-driven intelligent systems. 

The anomalous nondipolar and nonaxisymmetric magnetic fields of Uranus and Neptune have long challenged conventional views of planetary dynamos. A thin-shell dynamo conjecture captures the observed phenomena but leaves unexplained the fundamental material basis and underlying mechanism. Here we report extensive quantum-mechanical calculations of polymorphism in the hydrogen–oxygen system at the pressures and temperatures of the deep interiors of these ice giant planets (to >600 GPa and 7,000 K). The results reveal the surprising stability of solid and fluid trihydrogen oxide (H 3 O) at these extreme conditions. Fluid H 3 O is metallic and calculated to be stable near the cores of Uranus and Neptune. As a convecting fluid, the material could give rise to the magnetic field consistent with the thin-shell dynamo model proposed for these planets. H 3 O could also be a major component in both solid and superionic forms in other (e.g., nonconvecting) layers. The results thus provide a materials basis for understanding the enigmatic magnetic-field anomalies and other aspects of the interiors of Uranus and Neptune. These findings have direct implications for the internal structure, composition, and dynamos of related exoplanets. 

Mobility restriction is a crucial measure to control the transmission of the COVID-19. Research has shown that effective distance measured by the number of travelers instead of physical distance can capture and predict the transmission of the deadly virus. However, these efforts have been limited mainly to a single source of disease. Also, they have not been tested on finer spatial scales. Based on prior work of effective distances on the country level, we propose the multiple-source effective distance, a metric that captures the distance for the virus to propagate through the mobility network on the county level in the U.S. Then, we estimate how the change in the number of sources impacts the global mobility rate. Based on the findings, a new method is proposed to locate sources and estimate the arrival time of the virus. The new metric outperforms the original single-source effective distance in predicting the arrival time. Last, we select two potential sources and quantify the arrival time delay caused by the national emergency declaration. In doing so, we provide quantitative answers on the effectiveness of the national emergency declaration.

 

The successful fabrication of black phosphorene (Black-P) in 2014 and subsequent synthesis of layered black As 1−x P x alloys have inspired research into two-dimensional (2D) binary As–P compounds. The very recent success in growing blue phosphorene (Blue-P) further motivated exploration of 2D Blue-AsP materials. Here, using ab initio swarm-intelligence global minimum structure-searching methods, we have obtained a series of novel and energetically favored 2D Blue-AsP (denoted x-AsP, x = I, II, III, IV, V) compounds with As : P = 1 : 1 stoichiometry. They display similar honeycomb structures to Blue-P. Remarkably, the lowest-energy AsP monolayer, namely I-AsP, not only possesses a quasi-direct band gap (2.41 eV), which can be tuned to a direct and optimal gap for photovoltaic applications by in-plane strain, but also has an ultrahigh electronic mobility up to ∼7.4 × 10 4 cm 2 V −1 s −1 , far surpassing that of Blue-P, and also exhibits high absorption coefficients (×10 5 cm −1 ). Our simulations also show that 30 nm-thick I-AsP sheet-based cells have photovoltaic efficiency as high as ∼12%, and the I-AsP/CdSe heterostructure solar cells possess a power conversion efficiency as high as ∼13%. All these outstanding characteristics suggest the I-AsP sheet as a promising material for high-efficiency solar cells.