Organosulfates as Tracers for Secondary Organic Aerosol (SOA) Formation from 2‑Methyl-3-Buten-2-ol (MBO) in the Atmosphere

2-Methyl-3-buten-2-ol (MBO) is an important biogenic volatile organic compound (BVOC) emitted by pine trees and a potential precursor of atmospheric secondary organic aerosol (SOA) in forested regions. In the present study, hydroxyl radical (OH)-initiated oxidation of MBO was examined in smog chambers under varied initial nitric oxide (NO) and aerosol acidity levels. Results indicate measurable SOA from MBO under low-NO conditions. Moreover, increasing aerosol acidity was found to enhance MBO SOA. Chemical characterization of laboratory-generated MBO SOA reveals that an organosulfate species (C_5H_(12)O_6S, MW 200) formed and was substantially enhanced with elevated aerosol acidity. Ambient fine aerosol (PM_(2.5)) samples collected from the BEARPEX campaign during 2007 and 2009, as well as from the BEACHON-RoMBAS campaign during 2011, were also analyzed. The MBO-derived organosulfate characterized from laboratory-generated aerosol was observed in PM_(2.5) collected from these campaigns, demonstrating that it is a molecular tracer for MBO-initiated SOA in the atmosphere. Furthermore, mass concentrations of the MBO-derived organosulfate are well correlated with MBO mixing ratio, temperature, and acidity in the field campaigns. Importantly, this compound accounted for an average of 0.25% and as high as 1% of the total organic aerosol mass during BEARPEX 2009. An epoxide intermediate generated under low-NO conditions is tentatively proposed to produce MBO SOA

Blocking effect of twin boundaries on partial dislocation emission from void surfaces

Recent discovery that nanoscale twin boundaries can be introduced in ultrafine-grained metals to improve strength and ductility has renewed interest in the mechanical behavior and deformation mechanisms of these nanostructured materials. By controlling twin boundary spacing, the effect of twin boundaries on void growth is investigated by using atomistic simulation method. The strength is significantly enhanced due to the discontinuous slip system associated with these coherent interfaces. Atomic-scale mechanisms underlying void growth, as well as the interaction between twin boundaries and the void, are revealed in details

CEO Turnover Announcements and Information Frictions

This paper analyzes the market reaction to CEO turnover announcements in the presence of information frictions. We find that the market reaction to forced CEO turnover announcements is negatively related to the level of asymmetric information between a firm and its investors. No such relation exists for voluntary turnovers. We also find that in cases where information frictions are high, companies attempt to present forced turnover as voluntary and this behavior leads to a less negative market response. Overall, our results suggest that firms act strategically when disclosing information about CEO turnover to avoid a negative market reaction

Is ProtoPNet Really Explainable? Evaluating and Improving the Interpretability of Prototypes

ProtoPNet and its follow-up variants (ProtoPNets) have attracted broad research interest for their intrinsic interpretability from prototypes and comparable accuracy to non-interpretable counterparts. However, it has been recently found that the interpretability of prototypes can be corrupted due to the semantic gap between similarity in latent space and that in input space. In this work, we make the first attempt to quantitatively evaluate the interpretability of prototype-based explanations, rather than solely qualitative evaluations by some visualization examples, which can be easily misled by cherry picks. To this end, we propose two evaluation metrics, termed consistency score and stability score, to evaluate the explanation consistency cross images and the explanation robustness against perturbations, both of which are essential for explanations taken into practice. Furthermore, we propose a shallow-deep feature alignment (SDFA) module and a score aggregation (SA) module to improve the interpretability of prototypes. We conduct systematical evaluation experiments and substantial discussions to uncover the interpretability of existing ProtoPNets. Experiments demonstrate that our method achieves significantly superior performance to the state-of-the-arts, under both the conventional qualitative evaluations and the proposed quantitative evaluations, in both accuracy and interpretability. Codes are available at https://github.com/hqhQAQ/EvalProtoPNet