1,132 research outputs found

    Hybrid TDOA/AOA mobile user location for wideband CDMA cellular systems

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    Multi-Modality Multi-Scale Cardiovascular Disease Subtypes Classification Using Raman Image and Medical History

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    Raman spectroscopy (RS) has been widely used for disease diagnosis, e.g., cardiovascular disease (CVD), owing to its efficiency and component-specific testing capabilities. A series of popular deep learning methods have recently been introduced to learn nuance features from RS for binary classifications and achieved outstanding performance than conventional machine learning methods. However, these existing deep learning methods still confront some challenges in classifying subtypes of CVD. For example, the nuance between subtypes is quite hard to capture and represent by intelligent models due to the chillingly similar shape of RS sequences. Moreover, medical history information is an essential resource for distinguishing subtypes, but they are underutilized. In light of this, we propose a multi-modality multi-scale model called M3S, which is a novel deep learning method with two core modules to address these issues. First, we convert RS data to various resolution images by the Gramian angular field (GAF) to enlarge nuance, and a two-branch structure is leveraged to get embeddings for distinction in the multi-scale feature extraction module. Second, a probability matrix and a weight matrix are used to enhance the classification capacity by combining the RS and medical history data in the multi-modality data fusion module. We perform extensive evaluations of M3S and found its outstanding performance on our in-house dataset, with accuracy, precision, recall, specificity, and F1 score of 0.9330, 0.9379, 0.9291, 0.9752, and 0.9334, respectively. These results demonstrate that the M3S has high performance and robustness compared with popular methods in diagnosing CVD subtypes

    Nonline-of-sight error mitigation in mobile location

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    Cognition investigation and analysis of hand hygiene of nursing staff in pension institutions

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    Objective: We investigate and analyze the cognition of hand hygiene of nursing staff in nursing institutions. This method provides reference for improving the hand hygiene condition of nursing staff in nursing homes, and we put forward the feasible solution to this situation. Methods: 100 nurses from five nursing institutions in Changchun were investigated using a self-designed questionnaire, and the results were analyzed. Results: due to the most old-age care institutions personnel are less educated, rapid flow of talents, and the health care training from endowment organization are low frequency or not organized, so most of nursing staff think hand hygiene has nothing to do with the health of the elderly. They grasp the knowledge of some common hand washing, and hand washing before and after the elderly care is not ideal. The effects of hand washing have a number of factors, the main factor is that the pension institutions hand washing facilities incomplete, and in fact the nursing staff work very busy. Discussion: from the government to pension institutions should strengthen and pay more attention to the training of pension agency front-line care staff hand hygiene knowledge, increase the training of professional nursing practitioners, focus on bringing in Colleges and universities social science or medical science related, similar professional personnel and institutional strengthening management of washing hands, according to the actual conditions to improve the hand washing facilities, adhere to wash their hands properly, so as to avoid occurrence of handling of disease spread

    Toward targeted therapy in chemotherapy-resistant pancreatic cancer with a smart triptolide nanomedicine

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    Chemoresistance is the major impediment for treating pancreatic cancer. Herb-derived compound triptolide (TP) can inhibit proliferation of chemo-resistant pancreatic cancer (CPC) cell lines through multiple mechanisms, which exhibited superior anticancer efficacy compared with gemcitabine. However, toxicity due to non-specific exposure to healthy tissues hindered its clinical translation. Herein we successfully achieved targeting CPC cells and avoiding exposure to healthy tissues for TP by nucleolin-specific aptamer (AS1411) mediated polymeric nanocarrier. We conjugated AS1411 aptamer to carboxy terminated poly(ethylene glycol)–block–poly(d, l-lactide) (HOOC-PEG-PDLLA), then prepared AS1411-PEG-PDLLA micelle loading TP (AS-PPT) through solid dispersion technique. AS-PPT showed more antitumor activity than TP and equivalent specific binding ability with gemcitabine-resistant human pancreatic cancer cell (MIA PaCa-2) to AS1411 aptamer in vitro. Furthermore, we studied the distribution of AS-PPT (Cy3-labed TP) at tissue and cellular levels using biophotonic imaging technology. The results showed AS1411 facilitated TP selectively accumulating in tumor tissues and targeting CPC cells. The lifetime of the MIA PaCa-2 cell-bearing mice administrated with AS-PPT was efficiently prolonged than that of the mice subjected to the clinical anticancer drug Gemzar®in vivo. Such work provides a new strategy for overcoming the drug resistance of pancreatic cancer
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