Alien Registration- Ewing, James T. (Winslow, Kennebec County)

https://digitalmaine.com/alien_docs/16664/thumbnail.jp

Care and hitches for work horses

May, 1939."Revision of Circular 287.

Collidoscope: An Improved Tool for Computing Collisional Cross Sections with the Trajectory Method

Ion Mobility-Mass Spectrometry (IM-MS) can be a powerful tool for determining structural information about ions in the gas phase, from small covalent analytes to large, unfolded, and/or denatured proteins and complexes. For large biomolecular ions, which may have a wide variety of possible gas-phase conformations and multiple charge sites, quantitative, physically explicit modeling of collisional cross sections (CCSs) for comparison to IMS data can be challenging and time-consuming. We present a “trajectory method” (TM) based CCS calculator, named “Collidoscope”, which utilizes parallel processing and optimized trajectory sampling, and implements both He and N2 as collision gas options. Also included is a charge-placement algorithm for determining probable charge site configurations for protonated protein ions given an input geometry in pdb file format. Results from Collidoscope are compared to those from the current state-of-the-art CCS simulation suite, IMoS. Collidoscope CCSs are typically within 4% of IMoS values for ions with masses from ~18 Da to ~800 kDa. Collidoscope CCSs using x-ray crystal geometries are typically within a few percent of IM-MS experimental values for ions with mass up to ~3.5 kDa (melittin), and discrepancies for larger ions up to ~800 kDa (GroEL) are attributed in large part to changes in ion structure during and after the electrospray process. Due to its physically explicit modeling of scattering, computational efficiency, and accuracy, Collidoscope can be a valuable tool for IM-MS research, especially for large biomolecular ions

Extended Protein Ions are Formed by the Chain Ejection Model in Chemical Supercharging Electrospray Ionization

Supercharging electrospray ionization can be a powerful tool for increasing charge states in mass spectra and generating unfolded ion structures, yet key details of its mechanism remain unclear. The structures of highly extended protein ions and the mechanism of supercharging were investigated using ion mobility-mass spectrometry. Head-to-tail-linked polyubiquitins (Ubq1−11) were used to determine size and charge state scaling laws for unfolded protein ions formed by supercharging while eliminating amino acid composition as a potential confounding factor. Collisional cross section was found to scale linearly with mass for these ions and several other monomeric proteins, and the maximum observed charge state for each analyte scales with mass in agreement with an analytical charge state scaling law for protein ions with highly extended structures that is supported by experimental gas-phase basicities. These results indicate that these highly unfolded ions can be considered quasi-one-dimensional, and collisional cross sections modeled with the Trajectory Method in Collidoscope show that these ions are significantly more extended than linear α-helices but less extended than straight chains. The effect of internal disulfide bonds on the extent of supercharging was probed using bovine serum albumin, β-lactoglobulin, and lysozyme, each of which contains multiple internal disulfide bonds. Reduction of the disulfide bonds led to a marked increase in charge state upon supercharging without significantly altering folding in solution. This evidence supports a supercharging mechanism in which these proteins unfold before or during evaporation of the electrospray droplet and ionization occurs by the Chain Ejection Model

Nano-porosity in GaSb induced by swift heavy ion irradiation

Nano-porous structures form in GaSb after ion irradiation with 185 MeV Au ions. The porous layer formation is governed by the dominant electronic energy loss at this energy regime. The porous layer morphology differs significantly from that previously reported for low-energy, ion-irradiated GaSb. Prior to the onset of porosity, positron annihilation lifetime spectroscopy indicates the formation of small vacancy clusters in single ion impacts, while transmission electron microscopy reveals fragmentation of the GaSb into nanocrystallites embedded in an amorphous matrix. Following this fragmentation process, macroscopic porosity forms, presumably within the amorphous phase.The authors thank the Australian Research Council for support and the staff at the ANU Heavy Ion Accelerator Facility for their continued technical assistance. R.C.E. acknowledges the support from the Office of Basic Energy Sciences of the U.S. DOE (Grant No. DE-FG02-97ER45656)

The 4-H colt club

February, 1936."Cooperative Extension Work in Agriculture and Home Economics, University of Missouri, College of Agriculture and the United States Department of Agriculture Cooperating."Title from cover

π‐complexes of diborynes with main group atoms

We present herein an in‐depth study of complexes in which a molecule containing a boron‐boron triple bond is bound to tellurate cations. The analysis allows the description of these salts as true π complexes between the B−B triple bond and the tellurium center. These complexes thus extend the well‐known Dewar‐Chatt‐Duncanson model of bonding to compounds made up solely of p block elements. Structural, spectroscopic and computational evidence is offered to argue that a set of recently reported heterocycles consisting of phenyltellurium cations complexed to diborynes bear all the hallmarks of π‐complexes in the π‐complex/metallacycle continuum envisioned by Joseph Chatt. Described as such, these compounds are unique in representing the extreme of a metal‐free continuum with conventional unsaturated three-membered rings (cyclopropenes, azirenes, borirenes) occupying the opposite end

Semantic network analysis of vaccine sentiment in online social media.

OBJECTIVE: To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. BACKGROUND: Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. METHODS: We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. RESULTS: The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. CONCLUSION: Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage in the United States

Conducting robust ecological analyses with climate data

Although the number of studies discerning the impact of climate change on ecological systems continues to increase, there has been relatively little sharing of the lessons learnt when accumulating this evidence. At a recent workshop entitled ‘Using climate data in ecological research’ held at the UK Met Office, ecologists and climate scientists came together to discuss the robust analysis of climate data in ecology. The discussions identified three common pitfalls encountered by ecologists: 1) selection of inappropriate spatial resolutions for analysis; 2) improper use of publically available data or code; and 3) insufficient representation of the uncertainties behind the adopted approach. Here, we discuss how these pitfalls can be avoided, before suggesting ways that both ecology and climate science can move forward. Our main recommendation is that ecologists and climate scientists collaborate more closely, on grant proposals and scientific publications, and informally through online media and workshops. More sharing of data and code (e.g. via online repositories), lessons and guidance would help to reconcile differing approaches to the robust handling of data. We call on ecologists to think critically about which aspects of the climate are relevant to their study system, and to acknowledge and actively explore uncertainty in all types of climate data. And we call on climate scientists to make simple estimates of uncertainty available to the wider research community. Through steps such as these, we will improve our ability to robustly attribute observed ecological changes to climate or other factors, while providing the sort of influential, comprehensive analyses that efforts to mitigate and adapt to climate change so urgently require