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Quantifying how grain size and/or deviatoric stress impact (Mg,Fe)₂SiO₄phase stability is critical for advancing our understanding of subduction processes and deep-focus earthquakes. Here, we demonstrate that well-resolved X-ray diffraction patterns can be obtained on nano-grained thin films within laser-heated diamond anvil cells (DACs) at hydrostatic pressures up to 24 GPa and temperatures up to 2300 K. Combined with well-established literature processes for tuning thin film grain size, biaxial stress, and substrate identity, these results suggest that DAC-loaded thin films can be useful for determining how grain size, deviatoric stress, and/or the coexistence of other phases influence high-pressure phase stability. As such, this novel DAC-loaded thin film approach may find use in a variety of earth science, planetary science, solid-state physics, and materials science applications.

 

Combined with mobile monitoring devices, telehealth generates overwhelming data, which could cause clinician burnout and overlooking critical patient status. Developing novel and efficient ways to correctly triage such data will be critical to a successful telehealth adoption. We aim to develop an automated classification framework of existing nurses’ notes for each alert that will serve as a training dataset for a future alert triage system for telehealth programs.

We analyzed and developed a coding framework and a regular expression-based keyword match approach based on the information of 24 931 alert notes from a community-based telehealth program. We evaluated our automated alert triaging model for its scalability on a stratified sampling of 800 alert notes for precision and recall analysis.

We found 22 717 out of 24 579 alert notes (92%) belonging to at least one of the 17 codes. The evaluation of the automated alert note analysis using the regular expression-based information extraction approach resulted in an average precision of 0.86 (SD = 0.13) and recall 0.90 (SD = 0.13).

The high-performance results show the feasibility and the scalability potential of this approach in community-based, low-income older adult telehealth settings. The resulting coded alert notes can be combined with participants’ health monitoring results to generate predictive models and to triage false alerts. The findings build steps toward developing an automated alert triaging model to improve the identification of alert types in remote health monitoring and telehealth systems.

 

Enterotoxigenic Escherichia coli (ETEC) is the primary etiologic agent of traveler’s diarrhea and a major cause of diarrheal disease and death worldwide, especially in infants and young children. Despite significant efforts over the past several decades, an affordable vaccine that appreciably decreases mortality and morbidity associated with ETEC infection among children under the age of 5 years remains an unmet aspirational goal. Here, we describe robust, cost-effective biosynthetic routes that leverage glycoengineered strains of non-pathogenic E. coli or their cell-free extracts for producing conjugate vaccine candidates against two of the most prevalent O serogroups of ETEC, O148 and O78. Specifically, we demonstrate site-specific installation of O-antigen polysaccharides (O-PS) corresponding to these serogroups onto licensed carrier proteins using the oligosaccharyltransferase PglB from Campylobacter jejuni. The resulting conjugates stimulate strong O-PS-specific humoral responses in mice and elicit IgG antibodies that possess bactericidal activity against the cognate pathogens. We also show that one of the prototype conjugates decorated with serogroup O148 O-PS reduces ETEC colonization in mice, providing evidence of vaccine-induced mucosal protection. We anticipate that our bacterial cell-based and cell-free platforms will enable creation of multivalent formulations with the potential for broad ETEC serogroup protection and increased access through low-cost biomanufacturing. 

While our society accelerates its transition to the Internet of Things, billions of IoT devices are now linked to the network. While these gadgets provide enormous convenience, they generate a large amount of data that has already beyond the network’s capacity. To make matters worse, the data acquired by sensors on such IoT devices also include sensitive user data that must be appropriately treated. At the moment, the answer is to provide hub services for data storage in data centers. However, when data is housed in a centralized data center, data owners lose control of the data, since data centers are centralized solutions that rely on data owners’ faith in the service provider. In addition, edge computing enables edge devices to collect, analyze, and act closer to the data source, the challenge of data privacy near the edge is also a tough nut to crack. A large number of user information leakage both for IoT hub and edge made the system untrusted all along. Accordingly, building a decentralized IoT system near the edge and bringing real trust to the edge is indispensable and significant. To eliminate the need for a centralized data hub, we present a prototype of a unique, secure, and decentralized IoT framework called Reja, which is built on a permissioned Blockchain and an intrusion-tolerant messaging system ChiosEdge, and the critical components of ChiosEdge are reliable broadcast and BFT consensus. We evaluated the latency and throughput of Reja and its sub-module ChiosEdge. 

Supramolecular polymer gels are an evolving class of soft materials with a vast number of properties that can be tuned to desired applications. Despite continuous advances concerning polymer synthesis, sustainability or adaptability, a consistent understanding of the interplay between structure, dynamics, and diffusion processes within transient networks is lacking. In this study, the hierarchy of several relaxation processes is investigated, starting from a microscopic perspective of a single sticker dissociation event up to the center-of-mass diffusion of a star-shaped polymer building block on different length scales, as well as the resulting macroscopic mechanical response to applied external stress. In addition to that, a second focus is placed on the gel micro-structure that is analyzed by light scattering. Conversion of the dynamic light scattering (DLS) inverse length scale into real space allows for a combination of relaxation times with those obtained by forced Rayleigh scattering (FRS). For these investigations, a model-type metallo-supramolecular network consisting of narrowly dispersed tetra-arm poly(ethylene glycol)-terpyridine macromolecules that are interconnected via complexation with zinc ions is chosen. Assembling the obtained activation energies reveals that all complex dissociation-governed relaxation processes exhibit similar activation energies.