Functionalized hyperbranched polymers via olefin metathesis

Hyperbranched polymers are highly branched, three-dimensional macromolecules which are closely related to dendrimers and are typically prepared via a one-pot polycondensation of AB_(n≥2) monomers.^1 Although hyperbranched macromolecules lack the uniformity of monodisperse dendrimers, they still possess many attractive dendritic features such as good solubility, low solution viscosity, globular structure, and multiple end groups.^1-3 Furthermore, the usually inexpensive, one-pot synthesis of these polymers makes them particularly desirable candidates for bulk-material and specialty applications. Toward this end, hyperbranched polymers have been investigated as both rheology-modifying additives to conventional polymers and as substrate-carrying supports or multifunctional macroinitiators, where a large number of functional sites within a compact space becomes beneficial

Probing the C-H Activation of Linear and Cyclic Ethers at (PNP)Ir

Interaction of the amido/bis(phosphine)-supported (PNP)Ir fragment with a series of linear and cyclic ethers is shown to afford, depending on substrate, products of α,α-dehydrogenation (carbenes), α,β-dehydrogenation (vinyl ethers), or decarbonylation. While carbenes are exclusively obtained from tert-amyl methyl ether, sec-butyl methyl ether (SBME), n-butyl methyl ether (NBME), and tetrahydrofuran (THF), vinyl ethers or their adducts are observed upon reaction with diethyl ether and 1,4-dioxane. Decarbonylation occurs upon interaction of (PNP)Ir with benzyl methyl ether, and a mechanism is proposed for this unusual transformation, which occurs via a series of C−H, C−O, and C−C bond cleavage events. The intermediates characterized for several of these reactions as well as the α,α-dehydrogenation of tert-butyl methyl ether (MTBE) are used to outline a reaction pathway for the generation of PNP-supported iridium(I) carbene complexes, and it is shown that the long-lived, observable intermediates are substrate-dependent and differ for the related cases of MTBE and THF. Taken together, these findings highlight the variety of pathways utilized by the electron-rich, unsaturated (PNP)Ir fragment to stabilize itself by transferring electron density to ethereal substrates through oxidative addition and/or the formation of π-acidic ligands

The Legal Framework for Language Access in Healthcare Settings: Title VI and Beyond

Over the past few decades, the number and diversity of limited English speakers in the USA has burgeoned. With this increased diversity has come increased pressure—including new legal requirements—on healthcare systems and clinicians to ensure equal treatment of limited English speakers. Healthcare providers are often unclear about their legal obligations to provide language services. In this article, we describe the federal mandates for language rights in health care, provide a broad overview of existing state laws and describe recent legal developments in addressing language barriers. We conclude with an analysis of key policy initiatives that would substantively improve health care for LEP patients

Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. However, previous work often treats representation learning and anomaly prediction separately. In this paper, we propose autoencoder based one-class support vector machine (AE-1SVM) that brings OC-SVM, with the aid of random Fourier features to approximate the radial basis kernel, into deep learning context by combining it with a representation learning architecture and jointly exploit stochastic gradient descent to obtain end-to-end training. Interestingly, this also opens up the possible use of gradient-based attribution methods to explain the decision making for anomaly detection, which has ever been challenging as a result of the implicit mappings between the input space and the kernel space. To the best of our knowledge, this is the first work to study the interpretability of deep learning in anomaly detection. We evaluate our method on a wide range of unsupervised anomaly detection tasks in which our end-to-end training architecture achieves a performance significantly better than the previous work using separate training.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 201

ClaimChain: Improving the Security and Privacy of In-band Key Distribution for Messaging

The social demand for email end-to-end encryption is barely supported by mainstream service providers. Autocrypt is a new community-driven open specification for e-mail encryption that attempts to respond to this demand. In Autocrypt the encryption keys are attached directly to messages, and thus the encryption can be implemented by email clients without any collaboration of the providers. The decentralized nature of this in-band key distribution, however, makes it prone to man-in-the-middle attacks and can leak the social graph of users. To address this problem we introduce ClaimChain, a cryptographic construction for privacy-preserving authentication of public keys. Users store claims about their identities and keys, as well as their beliefs about others, in ClaimChains. These chains form authenticated decentralized repositories that enable users to prove the authenticity of both their keys and the keys of their contacts. ClaimChains are encrypted, and therefore protect the stored information, such as keys and contact identities, from prying eyes. At the same time, ClaimChain implements mechanisms to provide strong non-equivocation properties, discouraging malicious actors from distributing conflicting or inauthentic claims. We implemented ClaimChain and we show that it offers reasonable performance, low overhead, and authenticity guarantees.Comment: Appears in 2018 Workshop on Privacy in the Electronic Society (WPES'18

Impact of Precipitating Electrons and Magnetosphere-Ionosphere Coupling Processes on Ionospheric Conductance

Modeling of electrodynamic coupling between the magnetosphere and ionosphere depends on accurate specification of ionospheric conductances produced by auroral electron precipitation. Magnetospheric models determine the plasma properties on magnetic field lines connected to the auroral ionosphere, but the precipitation of energetic particles into the ionosphere is the result of a two step process. The first step is the initiation of electron precipitation into both magnetic conjugate points from Earths plasma sheet via wave-particle interactions. The second step consists of the multiple atmospheric reflections of electrons at the two magnetic conjugate points, which produces secondary superthermal electron fluxes. The steady state solution for the precipitating particle fluxes into the ionosphere differs significantly from that calculated based on the originating magnetospheric population predicted by MHD and ring current kinetic models. Thus, standard techniques for calculating conductances from the mean energy and energy flux of precipitating electrons in model simulations must be modified to account for these additional processes. Here we offer simple parametric relations for calculating Pedersen and Hall height-integrated conductances that include the contributions from superthermal electrons produced by magnetosphere-ionosphere-atmosphere coupling in the auroral regions

Probing Stereoselectivity in Ring-Opening Metathesis Polymerization Mediated by Cyclometalated Ruthenium-Based Catalysts: A Combined Experimental and Computational Study

The microstructures of polymers produced by ring-opening metathesis polymerization (ROMP) with cyclometalated Ru-carbene metathesis catalysts were investigated. A strong bias for a cis,syndiotactic microstructure with minimal head-to-tail bias was observed. In instances where trans errors were introduced, it was determined that these regions were also syndiotactic. Furthermore, hypothetical reaction intermediates and transition structures were analyzed computationally. Combined experimental and computational data support a reaction mechanism in which cis,syndio-selectivity is a result of stereogenic metal control, while microstructural errors are predominantly due to alkylidene isomerization via rotation about the Ru═C double bond

Using EPR To Compare PEG-branch-nitroxide “Bivalent-Brush Polymers” and Traditional PEG Bottle–Brush Polymers: Branching Makes a Difference

Attachment of poly(ethylene glycol) (PEG) to polymeric nanostructures is a general strategy for sterically shielding and imparting water solubility to hydrophobic payloads. In this report, we describe direct graft-through polymerization of branched, multifunctional macromonomers that possess a PEG domain and a hydrophobic nitroxide domain. Electron paramagnetic resonance (EPR) spectroscopy was used to characterize microenvironments within these novel nanostructures. Comparisons were made to nitroxide-labeled, traditional bottle-brush random and block copolymers. Our results demonstrate that bivalent bottle-brush polymers have greater microstructural homogeneity compared to random copolymers of similar composition. Furthermore, we found that compared to a traditional brush polymer, the branched-brush, “pseudo-alternating” microstructure provided more rotational freedom to core-bound nitroxides, and greater steric shielding from external reagents. The results will impact further development of multivalent bottle-brush materials as nanoscaffolds for biological applications

Dynamic evolution in the key honey bee pathogen deformed wing virus: Novel insights into virulence and competition using reverse genetics

The impacts of invertebrate RNA virus population dynamics on virulence and infection out- comes are poorly understood. Deformed wing virus (DWV), the main viral pathogen of honey bees, negatively impacts bee health, which can lead to colony death. Despite previ- ous reports on the reduction of DWV diversity following the arrival of the parasitic mite Var- roa destructor, the key DWV vector, we found high genetic diversity of DWV in infested United States honey bee colonies. Phylogenetic analysis showed that divergent US DWV genotypes are of monophyletic origin and were likely generated as a result of diversification after a genetic bottleneck. To investigate the population dynamics of this divergent DWV, we designed a series of novel infectious cDNA clones corresponding to coexisting DWV genotypes, thereby devising a reverse-genetics system for an invertebrate RNA virus qua- sispecies. Equal replication rates were observed for all clone-derived DWV variants in single infections. Surprisingly, individual clones replicated to the same high levels as their mixtures and even the parental highly diverse natural DWV population, suggesting that complemen- tation between genotypes was not required to replicate to high levels. Mixed clone–derived infections showed a lack of strong competitive exclusion, suggesting that the DWV geno- types were adapted to coexist. Mutational and recombination events were observed across clone progeny, providing new insights into the forces that drive and constrain virus diversifi- cation. Accordingly, our results suggest that Varroa influences DWV dynamics by causing an initial selective sweep, which is followed by virus diversification fueled by negative fre- quency-dependent selection for new genotypes. We suggest that this selection might reflect the ability of rare lineages to evade host defenses, specifically antiviral RNA interference (RNAi). In support of this hypothesis, we show that RNAi induced against one DWV strain is less effective against an alternate strain from the same population