Investigation of HNCO isomers formation in ice mantles by UV and thermal processing: an experimental approach

Current gas phase models do not account for the abundances of HNCO isomers detected in various environments, suggesting a formation in icy grain mantles. We attempted to study a formation channel of HNCO and its possible isomers by vacuum-UV photoprocessing of interstellar ice analogues containing H$_2$O, NH$_3$, CO, HCN, CH$_3$OH, CH$_4$, and N$_2$ followed by warm-up, under astrophysically relevant conditions. Only the H$_2$O:NH$_3$:CO and H$_2$O:HCN ice mixtures led to the production of HNCO species. The possible isomerization of HNCO to its higher energy tautomers following irradiation or due to ice warm-up has been scrutinized. The photochemistry and thermal chemistry of H$_2$O:NH$_3$:CO and H$_2$O:HCN ices was simulated using the Interstellar Astrochemistry Chamber (ISAC), a state-of-the-art ultra-high-vacuum setup. The ice was monitored in situ by Fourier transform mid-infrared spectroscopy in transmittance. A quadrupole mass spectrometer (QMS) detected the desorption of the molecules in the gas phase. UV-photoprocessing of H$_2$O:NH$_3$:CO/H$_2$O:HCN ices lead to the formation of OCN$^-$ as main product in the solid state and a minor amount of HNCO. The second isomer HOCN has been tentatively identified. Despite its low efficiency, the formation of HNCO and the HOCN isomers by UV-photoprocessing of realistic simulated ice mantles, might explain the observed abundances of these species in PDRs, hot cores, and dark clouds

Imposter Participants in Online Qualitative Interviews: A Protocol for Trauma-Informed and Equitable Decision-Making

Imposter participants are an emerging concern in qualitative research due to the recent increase in online recruitment and virtual interviews. Unfortunately, there is limited guidance on how to address imposter participants in an equitable, trauma-informed way. To bridge this gap, we share imposter participant red flags, challenges, and a protocol that provides questions to ask and possible activities to engage in throughout the research process from conceptualization through findings dissemination. We ground this guidance in examples from our recent study with LGBTQ+ (e.g., lesbian, gay, bisexual, transgender, queer) survivors of sexual and intimate partner violence

Towards durable multistakeholder-generated solutions: The pilot application of a problem-oriented policy learning protocol to legality verification and community rights in Peru

This paper reports and reflects on the pilot application of an 11-step policy learning protocol that was developed by Cashore and Lupberger (2015) based on several years of Cashore’s multi-author collaborations. The protocol was applied for the first time in Peru in 2015 and 2016 by the IUFRO Working Party on Forest Policy Learning Architectures (hereinafter referred to as the project team). The protocol integrates insights from policy learning scholarship (Hall 1993, Sabatier 1999) with Bernstein and Cashore’s (2000, 2012) four pathways of influence framework. The pilot implementation in Peru focused on how global timber legality verification interventions might be harnessed to promote local land rights. Legality verification focuses attention on the checking and auditing of forest management units in order to verify that timber is harvested and traded in compliance with the law. We specifically asked: How can community legal ownership of, and access to, forestland and forest resources be enhanced? The protocol was designed as a dynamic tool, the implementation of which fosters iterative rather than linear processes. It directly integrated two objectives: 1) identifying the causal processes through which global governance initiatives might be harnessed to produce durable results ‘on the ground’; 2) generating insights and strategies in collaboration with relevant stakeholders. This paper reviews and critically evaluates our work in designing and piloting the protocol. We assess what seemed to work well and suggest modifications, including an original diagnostic framework for nurturing durable change. We also assess the implications of the pilot application of the protocol for policy implementation that works to enhance the influence of existing international policy instruments, rather than contributing to fragmentation and incoherence by creating new ones

Evaluation of the degradation of fine asphalt-aggregate mixtures containing high reclaimed asphalt pavement contents

This paper evaluates the mechanical properties and performance of the fine aggregate matrix (FAM) existing within full reclaimed asphalt pavement (RAP) asphalt mixtures, in terms of their rheological and fatigue deterioration properties. The RAP material was produced in the laboratory to control its properties and to reduce the effects of variability associated with these materials. Four FAM mixtures were analysed, including a virgin hot mix asphalt, a 100%RAP, and two mixtures containing 50% RAP in combination with virgin materials using different penetration grade virgin binders. The analysis of the deterioration properties was based on the application of a fracture model that incorporates the viscoelastic properties of the material, the quality of the adhesive bonds developed between the aggregates and the corresponding bitumen present in each mixture, and the rate at which the material dissipates energy when subjected to cycling loading. The input parameters for this model include the results obtained from dynamic mechanical analysis and surface free energy tests. In general, the results showed that the incorporation of 50% RAP content increased the stiffness of the final mixtures, as expected. However, this hardening effect did not result in mixtures with inferior fatigue performance of the FAM present in the full mixtures, at the applied strain level

Control of Glycolytic Flux by AMPK and p53-Mediated Signaling Pathways in Tumor Cells Adapted to Grow at Low pH

Introduction: Tumor cells grow in nutrient and oxygen deprived microenvironments and adapt to the suboptimal growth conditions by altering metabolic pathways. This adaptation process characteristically results in a tumor phenotype that displays anaerobic glycolysis, chronic acidification and aggressive tumor characteristics. Understanding the tumor cell reaction to the microenvironment is a critical factor in predicting the tumor response to hyperthermia. The glucose regulatory molecule, 6-Phosphofructo-2-Kinase/Fructose-2,6-Biphosphatase Isoform-3 (PFKFB3), is a bifunctional enzyme central to glycolytic flux and downstream of the metabolic stress sensor AMP-activated protein kinase (AMPK), which has been shown to activate an isoform of Phosphofructokinase (PFK-2). Society for Thermal Medicine Annual Meeting April 23-26, Clearwater Beach, FL

Control of Glycolytic Flux by AMPK and p53-mediated Signaling Pathways in Tumor Cells Grown at Low pH

Introduction: Tumor cells grow in nutrient and oxygen deprived microenvironments and adapt to the suboptimal growth conditions by altering metabolic pathways. This adaptation process characteristically results in a tumor phenotype that displays upregulated Hif-1α anaerobic glycolysis, chronic acidification, reduced rate of overall protein synthesis, lower rate of cell proliferation and aggressive invasive characteristics. Most transplantable tumors exhibit a pHe of 6.7- 7.0; the DB-1 melanoma xenografts used here have a pHe=6.7. Understanding tumor cell reaction to the microenvironment is a critical factor in predicting the tumor response to radiotherapy. The glucose regulatory molecule, 6-Phosphofructo-2-Kinase/Fructose-2,6- Biphosphatase Isoform-3 (PFKFB3), is a bifunctional enzyme central to glycolytic flux and downstream of the metabolic stress sensor AMP-activated protein kinase (AMPK), which we show activates an isoform of phosphofructokinase (PFK-2). Radiation Research Society (RRS) 8th Annual Meeting September 25-29, Maui, H

A general-purpose machine learning Pt interatomic potential for an accurate description of bulk, surfaces and nanoparticles

A Gaussian approximation machine learning interatomic potential for platinum is presented. It has been trained on DFT data computed for bulk, surfaces and nanostructured platinum, in particular nanoparticles. Across the range of tested properties, which include bulk elasticity, surface energetics and nanoparticle stability, this potential shows excellent transferability and agreement with DFT, providing state-of-the-art accuracy at low computational cost. We showcase the possibilities for modeling of Pt systems enabled by this potential with two examples: the pressure-temperature phase diagram of Pt calculated using nested sampling and a study of the spontaneous crystallization of a large Pt nanoparticle based on classical dynamics simulations over several nanoseconds