1,555 research outputs found

    Public knowledge of how to use an automatic external defibrillator in out-of-hospital cardiac arrest in Hong Kong

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    Data driven discovery of cyber physical systems

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    Abstract: Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber-physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance

    Electrochemical determination of hydroquinone using hydrophobic ionic liquid-type carbon paste electrodes

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    Three types of carbon paste electrodes (CPEs) with different liquid binders were fabricated, and their electrochemical behavior was characterized via a potassium hexacyanoferrate(II) probe. 1-Octyl-3-methylimidazolium hexafluorophosphate ionic liquid (IL) as a hydrophobic conductive pasting binder showed better electrochemical performance compared with the commonly employed binder. The IL-contained CPEs demonstrated excellent electroactivity for oxidation of hydroquinone. A diffusion control mechanism was confirmed and the diffusion coefficient (D) of 5.05 Γ— 10-4 cm2 s-1 was obtained. The hydrophobic IL-CPE is promising for the determination of hydroquinone in terms of high sensitivity, easy operation, and good durability

    Psychological Disorders, Cognitive Dysfunction and Quality of Life in Nasopharyngeal Carcinoma Patients with Radiation-Induced Brain Injury

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    PURPOSE:To evaluate factors affecting psychology, cognitive function and quality of life (QOL) of nasopharyngeal carcinoma (NPC) patients with radiation-induced brain injury (RI). METHODS AND MATERIALS:46 recurrence-free NPC patients with RI and 46 matched control patients without RI were recruited in our study. Subjective and objective symptoms of RI were evaluated with the LENT/SOMA systems. Psychological assessment was measured with Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS). Montreal Cognitive Assessment (MoCA) was carried out in these patients for assessing their cognitive function. QOL was evaluated by means of WHOQOL BREF. RESULTS:Of the patients with RI, 39(84.8%) had depression and 40(87.0%) had anxiety. The patients with RI got higher scores both in SDS and SAS than those without RI (SDS, 63.48Β±8.11 vs. 58.67Β±7.52, pβ€Š=β€Š0.008; SAS, 67.36Β±10.41 vs. 60.34Β±9.76, pβ€Š=β€Š0.005). Score in MoCA of patients with RI was significantly lower than that of patients without RI (21.32Β±2.45 vs. 25.98Β±1.73, p<0.001). SAS was positive correlated with post-radiotherapy interval. Both SAS and SDS had a significantly positive correlation with the rank of SOMA, while MoCA had a significantly negative correlation with SOMA. Chemotherapy was a risk factor for cognitive dysfunction. In addition, patients with RI got significantly lower scores in physical health (16.50Β±11.05 vs. 35.02Β±10.43, p<0.001), psychological health (17.70Β±10.33 vs. 39.48Β±12.00, p<0.001) and social relationship (48.00Β±18.65 vs. 67.15Β±19.70, p<0.001) compared with those in patients without RI. Multiple linear regression analysis revealed that anxiety and cognitive impairment were significant predictors of global QOL. CONCLUSIONS:NPC patients with RI exhibit negative emotions, impaired cognitive function and QOL. The severity of clinical symptoms of RI plays an important role in both emotions and cognitive function. Anxiety and cognitive impairment are associated with decreased QOL

    Variational Methods for Biomolecular Modeling

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    Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrostatics and solvation that includes the curvature energy of the molecular surface, the formation of microdomains on lipid membrane due to the geometric and molecular mechanics at the lipid interface, and the mean curvature driven protein localization on membrane surfaces. By further implicitly representing the interface using a phase field function over the entire domain, one can simulate the dynamics of the interface and the corresponding energy variation by evolving the phase field function, achieving significant reduction of the number of degrees of freedom and computational complexity. Strategies for improving the efficiency of computational implementations and for extending applications to coarse-graining or multiscale molecular simulations are outlined.Comment: 36 page

    Targeted Delivery of Chemotherapy Agents Using a Liver Cancer-Specific Aptamer

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    Using antibody/aptamer-drug conjugates can be a promising method for decreasing toxicity, while increasing the efficiency of chemotherapy.In this study, the antitumor agent Doxorubicin (Dox) was incorporated into the modified DNA aptamer TLS11a-GC, which specifically targets LH86, a human hepatocellular carcinoma cell line. Cell viability tests demonstrated that the TLS11a-GC-Dox conjugates exhibited both potency and target specificity. Importantly, intercalating Dox into the modified aptamer inhibited nonspecific uptake of membrane-permeable Dox to the non-target cell line. Since the conjugates are selective for cells that express higher amounts of target proteins, both criteria noted above are met, making TLS11a-GC-Dox conjugates potential candidates for targeted delivery to liver cancer cells.Considering the large number of available aptamers that have specific targets for a wide variety of cancer cells, this novel aptamer-drug intercalation method will have promising implications for chemotherapeutics in general
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