Distributional effects of vehicle tax in the framework of transportation externalities

Figure S2.The relationship between perivascular CD4 infiltration and 12 months follow-up DLCO (p = 0.134, r = −0.205). (PPT 43 kb

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Red blood cell height displacemen

Learning Nominal Regular Languages with Binders

The theories of formal language and automata are fundamental in several areas of computer science. During decades of development, these theories have been stretched out and reach many branches and application contexts, ranging from lexical analysis, natural language processing, model checking, and system design. Recently, the applications of machine learning are spreading out rapidly. One interesting application, learning automata, gains sustained attention crossing the disciplines.This dissertation investigates learning nominal automata, an extension of classical automata to alphabets featuring names. This class of automata capture nominal regular languages; analogously to the classical language theory, nominal automata have been shown to characterise nominal regular expressions with binders. These formalisms are amenable to abtract modelling resource-aware computations.We propose nL*, a learning algorithm on nominal regular languages with binders. Our algorithm generalises Angluin's algorithm L* with respect to nominal regular languages with binders. We show the correctness of nL* and study its theoretical complexity.We also develop a implementation of nL* that we use to experimentally analyse different strategies for providing counterexamples to the learner. These strategies are designed on the base of the rich algebraic structure provided by our nominal setting. Further, we evaluate the behaviours of the process and its efficiency according tothe different strategies with a set of experiments.</div

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Red blood cell membrane fluctuatio

High-Throughput Approach Exploitation: Two-Dimensional Double-Metal Sulfide (M₂S₂) of Efficient Electrocatalysts for Oxygen Reduction Reaction in Fuel Cells

A transition-metal sulfide (M2S2) nanolayer as a catalyst for the oxygen reduction reaction (ORR) has been investigated by the density functional theory (DFT) method to explore the underlying mechanisms of the elementary reaction steps for the ORR process. Both the O2 dissociation and O2 hydrogenation paths are probably possible in the ORR on the M2S2 surface. All of the possible intermediate reaction steps of the ORR are exothermic for O2 hydrogenation. This indicates that the four-electron reaction path (4e– ORR) process is the most favorable path, and it is preferred over the two-electron path (2e– ORR) process. The changes in the reaction free energy diagrams were determined, and these diagrams showed that oxygen hydrogenation (OOH) is the rate-determining step. Meanwhile, different working potentials for our studied catalysts were also considered, and we observed that the double-transition-metal sulfide catalysts are energetically favorable (exothermic) catalysts via a 4e transfer mechanism of the ORR processes. According to the formation energies of the ORR intermediates (*O, *OH, *OOH) and the scaling relations between them on different slabs, the volcano plot for the overpotential of the catalyst is also an important index of the catalytic activities, and we found that a smaller overpotential is appropriate to determine better catalytic activities for the ORR process

Data_Sheet_1_Using Humor to Promote Social Distancing on Tiktok During the COVID-19 Pandemic.docx

BackgroundDuring the COVID-19 pandemic, many humorous videos on how to practice social distancing appeared on social media. However, the effect of using humor as a crisis communication strategy to persuade people to conform to social distancing rules is not known.ObjectiveDrawing on the literature on humorous message framing and crisis communication, this research explores the effectiveness of a humorous message in communicating social distancing rules in two crisis severity phases (low vs. high severity) and also evaluates how humor affects individuals’ online and offline engagement intentions during the COVID-19 pandemic.MethodsA 2 (message framing: humorous vs. non-humorous) x 2 (crisis severity phase: low vs. high) between-subjects design experiment was conducted to test the research questions during the first weeks of the COVID-19 pandemic in China from January 30 to February 2, 2020.ResultsThe results showed that the severity of the phase of a health crisis can significantly affect stakeholders’ online and offline responses toward the disease. More specifically, in a low severity phase, humor led to increased source likability for the message, and more online and offline engagement intentions. However, no differences between a humorous and non-humorous message in perceived risk were observed. Whereas, in a high severity crisis phase, humor reduced individuals’ offline engagement intentions and a decrease in perceived risk, no significant difference was found between a humorous and non-humorous message on source likeability.ConclusionHumor can motivate both more online engagement and offline protective action intention when the crisis severity phase is low, while when crisis severity soars, a non-humorous message should be more desirable. More specifically, using humor in communicating information about an infectious disease can enhance the spokesperson’s likeability in a low severity phase, and also helps to spread health information to a larger audience. While, the negative side of using humor in communicating an infectious disease appears in severe crisis phases, as it then decreased the public’s perception of risk, and triggers less protective actions. Going beyond previous research, this study recognized that crisis severity changes in different phases of the spread of infectious disease, thereby providing actionable strategy selections for crisis practitioners in a dynamic communication environment.</p

Systematic Study of <i>in Vitro</i> Selection Stringency Reveals How To Enrich High-Affinity Aptamers

Aptamers are oligonucleotide receptors with great potential for sensing and therapeutic applications. They are isolated from random libraries through an in vitro method termed systematic evolution of ligands by exponential enrichment (SELEX). Although SELEX-based methods have been widely employed over several decades, many aspects of the experimental process remain poorly understood in terms of how to adjust the selection conditions to obtain aptamers with the desired set of binding characteristics. As a result, SELEX is often performed with arbitrary parameters that tend to produce aptamers with insufficient affinity and/or specificity. Having a better understanding of these basic principles could increase the likelihood of obtaining high-quality aptamers. Here, we have systematically investigated how altering the selection stringency in terms of target concentrationwhich is essentially the root source of selection pressure for aptamer isolationaffects the outcome of SELEX. By performing four separate trials of SELEX for the same small-molecule target, we experimentally prove that the use of excessively high target concentrations promotes enrichment of low-affinity binders while also suppressing the enrichment of high-affinity aptamers. These findings should be broadly applicable across SELEX methods, given that they share the same core operating principle, and will be crucial for guiding selections to obtain high-quality aptamers in the future

Subtle Structural Translation Magically Modulates the Super-Resolution Imaging of Self-Blinking Rhodamines

The evolution of super-resolution imaging techniques is benefited from the ongoing competition for optimal rhodamine fluorophores. Yet, it seems blind to construct the desired rhodamine molecule matching the imaging need without the knowledge on imaging impact of even the minimum structural translation. Herein, we have designed a pair of self-blinking sulforhodamines (STMR and SRhB) with the bare distinction of methyl or ethyl substituents and engineered them with Halo protein ligands. Although the two possess similar spectral properties (λab, λfl, ϕ, etc.), they demonstrated unique single-molecule characteristics preferring to individual imaging applications. Experimentally, STMR with high emissive rates was qualified for imaging structures with rapid dynamics (endoplasmic reticulum, and mitochondria), and SRhB with prolonged on-times and photostability was suited for relatively “static” nuclei and microtubules. Using this new knowledge, the mitochondrial morphology during apoptosis and ferroptosis was first super-resolved by STMR. Our study highlights the significance of even the smallest structural modification to the modulation of super-resolution imaging performance and would provide insights for future fluorophore design

Results of antibody-antigen and dockground complexes predicted by ASPDock and SRM.

<p>Hit count and success rate are analyzed form top 2000 predictions of each complex. Relative interface area, UB-RMSD of receptors and ligands implicate the difficulty of prediction.</p