The Medical Authority of AI: A Study of AI-enabled Consumer-facing Health Technology

Recently, consumer-facing health technologies such as Artificial Intelligence (AI)-based symptom checkers (AISCs) have sprung up in everyday healthcare practice. AISCs solicit symptom information from users and provide medical suggestions and possible diagnoses, a responsibility that people usually entrust with real-person authorities such as physicians and expert patients. Thus, the advent of AISCs begs a question of whether and how they transform the notion of medical authority in everyday healthcare practice. To answer this question, we conducted an interview study with thirty AISC users. We found that users assess the medical authority of AISCs using various factors including automated decisions and interaction design patterns of AISC apps, associations with established medical authorities like hospitals, and comparisons with other health technologies. We reveal how AISCs are used in healthcare delivery, discuss how AI transforms conventional understandings of medical authority, and derive implications for designing AI-enabled health technology

Isolation of Thylakoid Membrane Complexes from Rice by a New Double-Strips BN/SDS-PAGE and Bioinformatics Prediction of Stromal Ridge Subunits Interaction

Thylakoid membrane complexes of rice (Oryza sativa L.) play crucial roles in growth and crop production. Understanding of protein interactions within the complex would provide new insights into photosynthesis. Here, a new “Double-Strips BN/SDS-PAGE” method was employed to separate thylakoid membrane complexes in order to increase the protein abundance on 2D-gels and to facilitate the identification of hydrophobic transmembrane proteins. A total of 58 protein spots could be observed and subunit constitution of these complexes exhibited on 2D-gels. The generality of this new approach was confirmed using thylakoid membrane from spinach (Spinacia oleracea) and pumpkin (Cucurita spp). Furthermore, the proteins separated from rice thylakoid membrane were identified by the mass spectrometry (MS). The stromal ridge proteins PsaD and PsaE were identified both in the holo- and core- PSI complexes of rice. Using molecular dynamics simulation to explore the recognition mechanism of these subunits, we showed that salt bridge interactions between residues R19 of PsaC and E168 of PasD as well as R75 of PsaC and E91 of PsaD played important roles in the stability of the complex. This stromal ridge subunits interaction was also supported by the subsequent analysis of the binding free energy, the intramolecular distances and the intramolecular energy

Globalization, Employment and Agriculture: A Review of the Eleventh Forum of the World Association for Political Economy

Economic globalization has greatly affected the economy, society and other aspects of individual countries and the world as a whole. As is well known, agriculture is the important foundation of the global economy, and most developing countries have a large rural population where agriculture is a significant part of the economy. Employment is the foundation of people's livelihood and full employment is difficult to achieve. Therefore, the study of how economic globalization affects agriculture and employment, and how developing countries and socialist countries should respond rationally and effectively, is worthy of attention

ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields

Neural Radiance Fields (NeRF) have achieved great success in the task of synthesizing novel views that preserve the same resolution as the training views. However, it is challenging for NeRF to synthesize high-quality high-resolution novel views with low-resolution training data. To solve this problem, we propose a zero-shot super-resolution training framework for NeRF. This framework aims to guide the NeRF model to synthesize high-resolution novel views via single-scene internal learning rather than requiring any external high-resolution training data. Our approach consists of two stages. First, we learn a scene-specific degradation mapping by performing internal learning on a pretrained low-resolution coarse NeRF. Second, we optimize a super-resolution fine NeRF by conducting inverse rendering with our mapping function so as to backpropagate the gradients from low-resolution 2D space into the super-resolution 3D sampling space. Then, we further introduce a temporal ensemble strategy in the inference phase to compensate for the scene estimation errors. Our method is featured on two points: (1) it does not consume high-resolution views or additional scene data to train super-resolution NeRF; (2) it can speed up the training process by adopting a coarse-to-fine strategy. By conducting extensive experiments on public datasets, we have qualitatively and quantitatively demonstrated the effectiveness of our method

Reshapeable, rehealable and recyclable sensor fabricated by direct ink writing of conductive composites based on covalent adaptable network polymers

Covalent adaptable network (CAN) polymers doped with conductive nanoparticles are an ideal candidate to create reshapeable, rehealable, and fully recyclable electronics. On the other hand, 3D printing as a deterministic manufacturing method has a significant potential to fabricate electronics with low cost and high design freedom. In this paper, we incorporate a conductive composite consisting of polyimine CAN and multi-wall carbon nanotubes into direct-ink-writing 3D printing to create polymeric sensors with outstanding reshaping, repairing, and recycling capabilities. The developed printable ink exhibits good printability, conductivity, and recyclability. The conductivity of printed polyimine composites is investigated at different temperatures and deformation strain levels. Their shape-reforming and Joule heating-induced interfacial welding effects are demonstrated and characterized. Finally, a temperature sensor is 3D printed with defined patterns of conductive pathways, which can be easily mounted onto 3D surfaces, repaired after damage, and recycled using solvents. The sensing capability of printed sensors is maintained after the repairing and recycling. Overall, the 3D printed reshapeable, rehealable, and recyclable sensors possess complex geometry and extend service life, which assist in the development of polymer-based electronics toward broad and sustainable applications. &nbsp;</p

Sol-Gel Derived Tungsten Doped VO₂ Thin Films on Si Substrate with Tunable Phase Transition Properties

Vanadium dioxide (VO2) with semiconductor-metal phase transition characteristics has presented great application potential in various optoelectrical smart devices. However, the preparation of doped VO2 film with a lower phase transition threshold on Si substrate needs more investigation for the exploration of silicon-based VO2 devices. In this work, the VO2 films doped with different contents of W element were fabricated on high-purity Si substrate, assisted with a post-annealing process. The films exhibited good crystallinity and uniform thickness. The X-ray diffraction and X-ray photoelectron spectroscopy characterizations illustrated that W element can be doped into the lattice of VO2 and lead to small lattice distortion. In turn, the in situ FT-IR measurements indicated that the phase transition temperature of the VO2 films can be decreased continuously with W doping content. Simultaneously, the doping would lead to largely enhanced conductivity in the film, which results in reduced optical transmittance. This work provides significant insights into the design of doped VO2 films for silicon-based devices

Additional file 1: Table S1. of Molecular dynamics simulation and bioinformatics study on chloroplast stromal ridge complex from rice (Oryza sativa L.)

Identification of the PsaC and PsaD proteins from the NCBI database in this study. Sequence identity to OsPsaC and OsPsaD were listed. Table S2. Identification of the psaC and psaD genes from the NCBI database in this study. Sequence identity to OspsaC and OspsaD were listed. Figure S1. Phylogenetic tree of the PsaC proteins. The numbers associated with the branches are bootstrap values. Species names are color-coded as follows: green → land plants, light green → charophyte, blue → pteridophyta, light blue → bryophyta, purple → green algae, and black → cyanobacteria. The tree was deposited in TreeBASE under submission ID 18661. Figure S2. Phylogenetic tree of PsaD proteins. The numbers associated with the branches are bootstrap values. Species names are color-coded as follows: green → land plants, light green → bryophyta, black → phaeocystis, and blue → green algae. The tree was deposited in TreeBASE under submission ID 18661. Figure S3. Sequences alignments of the psaC genes. The sequences encoding R19 and D47 are highlighted. The color code indicates consistency between pairwise alignments (red: high, yellow: middle, blue: low). Figure S4. Sequences alignments of the psaD genes. The sequences encoding K62 and E103 are highlighted. The color code indicates consistency between pairwise alignments (red: high, yellow: middle, blue: low). Figure S5. Two docking models are superimposed with the MD model. Two salt bridges R19-E103 and D47-K62 are highlighted in their vdW representations. (DOCX 1149 kb