Influence of particle-phase state on the hygroscopic behavior of mixed organic-inorganic aerosols

Recent work has demonstrated that organic and mixed organic–inorganic particles can exhibit multiple phase states depending on their chemical composition and on ambient conditions such as relative humidity (RH). To explore the extent to which water uptake varies with particle-phase behavior, hygroscopic growth factors (HGFs) of nine laboratory-generated, organic and organic–inorganic aerosol systems with physical states ranging from well-mixed liquids to phase-separated particles to viscous liquids or semi-solids were measured with the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe at RH values ranging from 40 to 90%. Water-uptake measurements were accompanied by HGF and RH-dependent thermodynamic equilibrium calculations using the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model. In addition, AIOMFAC-predicted growth curves are compared to several simplified HGF modeling approaches: (1) representing particles as ideal, well-mixed liquids; (2) forcing a single phase but accounting for non-ideal interactions through activity coefficient calculations; and (3) a Zdanovskii–Stokes–Robinson-like calculation in which complete separation of the inorganic and organic components is assumed at all RH values, with water uptake treated separately in each of the individual phases. We observed variability in the characteristics of measured hygroscopic growth curves across aerosol systems with differing phase behaviors, with growth curves approaching smoother, more continuous water uptake with decreasing prevalence of liquid–liquid phase separation and increasing oxygen : carbon ratios of the organic aerosol components. We also observed indirect evidence for the dehydration-induced formation of highly viscous semi-solid phases and for kinetic limitations to the crystallization of ammonium sulfate at low RH for sucrose-containing particles. AIOMFAC-predicted growth curves are generally in good agreement with the HGF measurements. The performances of the simplified modeling approaches, however, differ for particles with differing phase states. This suggests that no single simplified modeling approach can be used to capture the water-uptake behavior for the diversity of particle-phase behavior expected in the atmosphere. Errors in HGFs calculated with the simplified models are of sufficient magnitude to produce substantial errors in estimates of particle optical and radiative properties, particularly for the assumption that water uptake is driven by absorptive equilibrium partitioning with ideal particle-phase mixing

Cleavable Biotin Probes for Labeling of Biomolecules via Azide−Alkyne Cycloaddition

The azide−alkyne cycloaddition provides a powerful tool for bio-orthogonal labeling of proteins, nucleic acids, glycans, and lipids. In some labeling experiments, e.g., in proteomic studies involving affinity purification and mass spectrometry, it is convenient to use cleavable probes that allow release of labeled biomolecules under mild conditions. Five cleavable biotin probes are described for use in labeling of proteins and other biomolecules via azide−alkyne cycloaddition. Subsequent to conjugation with metabolically labeled protein, these probes are subject to cleavage with either 50 mM Na_2S_2O_4, 2% HOCH_2CH_2SH, 10% HCO_2H, 95% CF_3CO_2H, or irradiation at 365 nm. Most strikingly, a probe constructed around a dialkoxydiphenylsilane (DADPS) linker was found to be cleaved efficiently when treated with 10% HCO_2H for 0.5 h. A model green fluorescent protein was used to demonstrate that the DADPS probe undergoes highly selective conjugation and leaves a small (143 Da) mass tag on the labeled protein after cleavage. These features make the DADPS probe especially attractive for use in biomolecular labeling and proteomic studies

Linear Logic Programming for Narrative Generation

Abstract. In this paper, we explore the use of Linear Logic programming for story generation. We use the language Celf to represent narrative knowledge, and its own querying mechanism to generate story instances, through a number of proof terms. Each proof term obtained is used, through a resource-flow analysis, to build a directed graph where nodes are narrative actions and edges represent inferred causality relationships. Such graphs represent narrative plots structured by narrative causality. Building on previous work evidencing the suitability of Linear Logic as a conceptual model of action and change for narratives, we explore the conditions under which these representations can be operationalized through Linear Logic Programming techniques. This approach is a candidate technique for narrative generation which unifies declarative representations and generation via query and deduction mechanisms

Deductive synthesis of recursive plans in linear logic

Linear logic has previously been shown to be suitable for describing and deductively solving planning problems involving conjunction and disjunction. We introduce a recursively defined datatype and a corresponding induction rule, thereby allowing recursive plans to be synthesised. In order to make explicit the relationship between proofs and plans, we enhance the linear logic deduction rules to handle plans as a form of proof term

A study on the friendship paradox – quantitative analysis and relationship with assortative mixing

The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the strength of the paradox and the direction of the paradox from the perspective of individual nodes, i.e., an indication of whether the individual is more or less popular than its friends. These local metrics are aggregated, and global metrics are proposed to express the phenomenon on a network-wide level. Theoretical results show that the defined metrics are well-behaved enough to capture the friendship paradox. We also theoretically analyze the behavior of the friendship paradox for popular network models in order to understand regimes where friendship paradox occurs. These theoretical findings are complemented by experimental results on both network models and real-world networks. By conducting a correlation study between the proposed metrics and degree assortativity, we experimentally demonstrate that the phenomenon of the friendship paradox is related to the well-known phenomenon of assortative mixing

Dopaminergic modulation of the hippocampal neuropil proteome identified by bioorthogonal noncanonical amino acid tagging (BONCAT)

Local protein synthesis and its activity-dependent modulation via dopamine receptor stimulation play an important role in synaptic plasticity – allowing synapses to respond dynamically to changes in their activity patterns. We describe here the metabolic labeling, enrichment, and MS-based identification of candidate proteins specifically translated in intact hippocampal neuropil sections upon treatment with the selective D1/D5 receptor agonist SKF81297. Using the noncanonical amino acid azidohomoalanine and click chemistry, we identified over 300 newly synthesized proteins specific to dendrites and axons. Candidates specific for the SKF81297-treated samples were predominantly involved in protein synthesis and synapse-specific functions. Furthermore, we demonstrate a dendrite-specific increase in proteins synthesis upon application of SKF81297. This study provides the first snapshot in the dynamics of the dopaminergic hippocampal neuropil proteome