Study on the Influencing Factors of Health Information Sharing Behavior of the Elderly under the Background of Normalization of Pandemic Situation

This study aims to solve the problem of unwise judgment, decisions, and correspondingly dangerous behaviors caused by error health information to the elderly. Based on the MOA model and self-determination theory, this paper constructs a health information sharing model for the elderly and analyzes it with Amos\u27s structural equation model. The study finds that media richness, health information literacy, perceived benefits, and negative emotions of the coronavirus epidemic positively influence health information sharing behavior. In contrast, perceived risks have a significant negative impact on health information sharing behavior. At the same time, media richness positively affects health information literacy, perceived benefits, and negative emotions of the coronavirus epidemic but has no significant impact on perceived risks. Health literacy positively affects perceived benefits but does not significantly affect the perceived risks and negative emotions of the coronavirus epidemic. This study aims to assist government and online social platforms in taking relevant measures under the background of normalization of the pandemic situation, controlling the spread of error health information among the elderly, and guiding the elderly to share health information better

Prognostic nomogram for bladder cancer with brain metastases: a National Cancer Database analysis.

BACKGROUND: This study aimed to establish and validate a nomogram for predicting brain metastasis in patients with bladder cancer (BCa) and assess various treatment modalities using a primary cohort comprising 234 patients with clinicopathologically-confirmed BCa from 2004 to 2015 in the National Cancer Database. METHODS: Machine learning method and Cox model were used for nomogram construction. For BCa patients with brain metastasis, surgery of the primary site, chemotherapy, radiation therapy, palliative care, brain confinement of metastatic sites, and the Charlson/Deyo Score were predictive features identified for building the nomogram. RESULTS: For the original 169 patients considered in the model, the areas under the receiver operating characteristic curve (AUC) were 0.823 (95% CI 0.758-0.889, P \u3c 0.001) and 0.854 (95% CI 0.785-0.924, P \u3c 0.001) for 0.5- and 1-year overall survival respectively. In the validation cohort, the nomogram displayed similar AUCs of 0.838 (95% CI 0.738-0.937, P \u3c 0.001) and 0.809 (95% CI 0.680-0.939, P \u3c 0.001), respectively. The high and low risk groups had median survivals of 1.91 and 5.09 months for the training cohort and 1.68 and 8.05 months for the validation set, respectively (both P \u3c 0.0001). CONCLUSIONS: Our prognostic nomogram provides a useful tool for overall survival prediction as well as assessing the risk and optimal treatment for BCa patients with brain metastasis

Detection of incoherent broadband terahertz light using antenna-coupled high-electron-mobility field-effect transistors

The sensitivity of direct terahertz detectors based on self-mixing of terahertz electromagnetic wave in field-effect transistors is being improved with noise-equivalent power close to that of Schottky-barrier-diode detectors. Here we report such detectors based on AlGaN/GaN two-dimensional electron gas at 77~K are able to sense broadband and incoherent terahertz radiation. The measured photocurrent as a function of the gate voltage agrees well with the self-mixing model and the spectral response is mainly determined by the antenna. A Fourier-transform spectrometer equipped with detectors designed for 340, 650 and 900~GHz bands allows for terahertz spectroscopy in a frequency range from 0.1 to 2.0~THz. The 900~GHz detector at 77~K offers an optical sensitivity about $1~\mathrm{pW/\sqrt{Hz}}$ being comparable to a commercial silicon bolometer at 4.2~K. By further improving the sensitivity, room-temperature detectors would find applications in active/passive terahertz imaging and terahertz spectroscopy.Comment: 4.5 pages, 5 figure

Artificial Intelligence based Building Attributes Enrichment in OpenStreetMap using Street-view Images

This work aims to improve OSM building attributes using street-view images. As OSM data are open and street-level photos can be taken with standard cell phones, our approach is neither geospatially restricted nor economically discriminated. In addition, crowdsourced platforms, such as Flickr, Unsplash, and Mapillary, provide huge amounts of street-view images that contain valuable building attribute information. We seek to facilitate open data and citizen science and encourage people to map for their communities

Viruses mobilize plant immunity to deter nonvector insect herbivores.

A parasite-infected host may promote performance of associated insect vectors; but possible parasite effects on nonvector insects have been largely unexplored. Here, we show that Begomovirus, the largest genus of plant viruses and transmitted exclusively by whitefly, reprogram plant immunity to promote the fitness of the vector and suppress performance of nonvector insects (i.e., cotton bollworm and aphid). Infected plants accumulated begomoviral βC1 proteins in the phloem where they were bound to the plant transcription factor WRKY20. This viral hijacking of WRKY20 spatiotemporally redeployed plant chemical immunity within the leaf and had the asymmetrical benefiting effects on the begomoviruses and its whitefly vectors while negatively affecting two nonvector competitors. This type of interaction between a parasite and two types of herbivores, i.e., vectors and nonvectors, occurs widely in various natural and agricultural ecosystems; thus, our results have broad implications for the ecological significance of parasite-vector-host tripartite interactions