231 research outputs found

    Advance Directive and End-of-Life Care Preferences Among Nursing Home Residents in Wuhan, China: A Cross-Sectional Study

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    © 2014 AMDA - The Society for Post-Acute and Long-Term Care Medicine. Objectives: To describe Chinese nursing home residents' knowledge of advance directive (AD) and end-of-life care preferences and to explore the predictors of their preference for AD. Design: Population-based cross-sectional survey. Settings: Nursing homes (n= 31) in Wuhan, Mainland Southern China. Participants: Cognitively intact nursing home residents (n= 467) older than 60 years. Measures: Face-to-face questionnaire interviews were used to collect information on demographics, chronic diseases, life-sustaining treatment, AD, and other end-of-life care preferences. Results: Most (95.3%) had never heard of AD, and fewer than one-third (31.5%) preferred to make an AD. More than half (52.5%) would receive life-sustaining treatment if they sustained a life-threatening condition. Fewer than one-half (43.3%) chose doctors as the surrogate decision maker about life-sustaining treatment, whereas most (78.8%) nominated their eldest son or daughter as their proxy. More than half (58.2%) wanted to live and die in their present nursing homes. The significant independent predictors of AD preference included having heard of AD before (odds ratio [OR] 9.323), having definite answers of receiving (OR 3.433) or rejecting (OR 2.530) life-sustaining treatment, and higher Cumulative Illness Rating Scale score (OR 1.098). Conclusions: Most nursing home residents did not know about AD, and nearly one-third showed positive attitudes toward it. AD should be promoted in mainland China. Education of residents, the proxy decision maker, and nursing home staff on AD is very important. Necessary policy support, legislation, or practice guidelines about AD should be made with flexibility to respect nursing home residents' rights in mainland China

    Genetic diversity among Toxoplasma gondii isolates from different hosts and geographical locations revealed by analysis of ROP13 gene sequences

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    Toxoplasma gondii can infect almost all the warm-blooded animals and human beings, causing serious public health problems and economic losses worldwide. Rhoptry protein 13 (ROP13) plays some roles in the invasion process of T. gondii. In this study, sequence variation in ROP13 gene among 14 T. gondii isolates from different geographical locations and hosts was examined. The ROP13 gene was amplified from individual isolates and sequenced. Results show that the length of the ROP13 sequences was 1203 bp. In total, there were 44 variable nucleotide positions in the ROP13 sequences, and sequence variations were 0.1 to 2.0% among the 14 examined T. gondii isolates, representing higher rate in transversion than in transition. Intra-specific nucleotide variations were mainly at the second codon positions. Phylogenetic analysis of the 14 examined T. gondii isolates indicate that the ROP13 sequence was not a suitable genetic marker to differentiate T. gondii isolates of different genotypes from different hosts and geographical regions. Low variation in ROP13 gene sequence may suggest that ROP13 gene could represent a good vaccine candidate against toxoplasmosis.Key words: Toxoplasma gondii, toxoplasmosis, rhpotry protein 13 (ROP13), sequence variation, phylogenetic analysis

    Wide Area Measuring System Signals Based Nonlinear Robust Adaptive DC Power Modulation Controller in AC/DC Interconnected Power System

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    The robust adaptive control law is proposed for a HVDC power modulation controller of the interconnected AC/DC power system. Based on the design idea of driving the center of inertia (COI) of different areas to a stable equilibrium point, the proposed controller is applied to damp inter-area oscillation of interconnected AC/ DC system using global signals of a wide area measuring system (WAMS). Designed by the back-stepping method, the robust adaptive control law is adaptive to the unknown parameters and is robust to model error, disturbances and different equilibrium points. Computer results show that the controller proposed is obviously superior to the conventional DC power modulation controller in damping inter-area oscillation and enhancing the power transfer limit. In addition, its performance can well adapt to the change of the equilibrium point. 設計了應用于交直流互聯電力系統的直流功率調制的非線性魯棒自適應控制器。該控制器基于驅動各互聯區域電網的慣量中心至統一平衡點的設計思想,采用廣域測量系統的全局信號,用以阻尼交直流互聯系統的區域間功率振蕩。采用反步法設計的自適應魯棒控制規律使控制器對未知參數具有自適應性,對模型誤差、擾動和平衡點變化具有較強的魯棒性。仿真結果表明,與傳統的線性直流功率調制控制器相比,該控制器對聯絡線的功率振蕩具有優良的阻尼性能,可顯著提高輸電極限,而且能很好地適應運行點的變化。link_to_OA_fulltex

    STUDY OF PALLADIUM ANALYTE BINARY-SYSTEM IN THE GRAPHITE-FURNACE BY SURFACE ANALYTICAL TECHNIQUES

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    The mechanisms of the stabilization of Pb, Zn and As by a palladium modifier were investigated by scanning electron microscopy, X-ray diffraction spectrometry and X-ray photoelectron spectrometry. All three elements were found to form an intermetallic solid solution with excess of Pd. The concentration ratio of Pd to analyte varies with the surface depth of Pd-analyte species. Chemical shifts measured in the binding energy of Pd and analyte are insignificant. The monophase of the Pd lattice in which some Pd atoms are displaced by the analyte atoms has been identified as being dominant. It is suggested that the reduced Pd and analyte form a stable intermetallic solid solution during the ashing stage and the analyte atoms remain in the Pd lattice until the temperature is high enough to break down the lattice

    Facile Synthesis of High Quality Graphene Nanoribbons

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    Graphene nanoribbons have attracted attention for their novel electronic and spin transport properties1-6, and because nanoribbons less than 10 nm wide have a band gap that can be used to make field effect transistors. However, producing nanoribbons of very high quality, or in high volumes, remains a challenge. Here, we show that pristine few-layer nanoribbons can be produced by unzipping mildly gas-phase oxidized multiwalled carbon nanotube using mechanical sonication in an organic solvent. The nanoribbons exhibit very high quality, with smooth edges (as seen by high-resolution transmission electron microscopy), low ratios of disorder to graphitic Raman bands, and the highest electrical conductance and mobility reported to date (up to 5e2/h and 1500 cm2/Vs for ribbons 10-20 nm in width). Further, at low temperature, the nanoribbons exhibit phase coherent transport and Fabry-Perot interference, suggesting minimal defects and edge roughness. The yield of nanoribbons was ~2% of the starting raw nanotube soot material, which was significantly higher than previous methods capable of producing high quality narrow nanoribbons1. The relatively high yield synthesis of pristine graphene nanoribbons will make these materials easily accessible for a wide range of fundamental and practical applications.Comment: Nature Nanotechnology in pres

    Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives

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    [EN] Digital transformation provide supply chains (SCs) with extensive accurate data that should be combined with analytical techniques to improve their management. Among these techniques Artificial Intelligence (AI) has proved their suitability, memory and ability to manage uncertain and constantly changing information. Despite the fact that a number of AI literature reviews exist, no comprehensive review of reviews for the SC operations planning has yet been conducted. This paper aims to provide a comprehensive review of AI literature reviews in a structured manner to gain insights into their evolution in incorporating new ICTs and collaboration. Results show that hybrization man-machine and collaboration and ethical aspects are understudied.This research has been funded by the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE). The first author was supported by the Generalitat Valenciana (Conselleria de Educación, Investigación, Cultura y Deporte) under Grant ACIF/2019/021.Rodríguez-Sánchez, MDLÁ.; Alemany Díaz, MDM.; Boza, A.; Cuenca, L.; Ortiz Bas, Á. (2020). Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives. IFIP Advances in Information and Communication Technology. 598:365-378. https://doi.org/10.1007/978-3-030-62412-5_30S365378598Lezoche, M., Hernandez, J.E., Alemany, M.M.E., Díaz, E.A., Panetto, H., Kacprzyk, J.: Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture. Comput. Ind. 117, 103–187 (2020)Stock, J.R., Boyer, S.L.: Developing a consensus definition of supply chain management: a qualitative study. Int. J. Phys. Distrib. Logistics Manag. 39(8), 690–711 (2009)Min, H.: Artificial intelligence in supply chain management: theory and applications. Int. J. Logistics Res. Appl. 13(1), 13–39 (2010). https://doi.org/10.1080/13675560902736537Hariri, R.H., Fredericks, E.M., Bowers, K.M.: Uncertainty in big data analytics: survey, opportunities, and challenges. J. Big Data 6(1), 1–16 (2019). https://doi.org/10.1186/s40537-019-0206-3Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. Int. J. Inf. Manage. 48(2019), 63–71 (2019). https://doi.org/10.1016/j.ijinfomgt.2019.01.021McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence. AI Mag. 27(4), 12–14 (2006)Barr, A., Feigenbaum, E.A.: The Handbook of Artificial Intelligence, vol. 2. Heuristech: William Kaufmann, Pitman (1982)High-Level Expert Group on Artificial Intelligence, European Commission. A definition of AI: main capabilities and disciplines (2019)Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., De Felice, F.: Artificial intelligence and machine learning applications in smart production: progress, trends, and directions. Sustainability (Switzerland) 12(2) (2020). https://doi.org/10.3390/su12020492Cheng, L., Yu, T.: A new generation of AI: a review and perspective on machine learning technologies applied to smart energy and electric power systems. Int. J. Energy Res. 43(6), 1928–1973 (2019). https://doi.org/10.1002/er.4333Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision-making in the era of big data. Evolution, challenges and research agenda. Int. J. Inf. Manag. 48, 63–71 (2019)Varshney, S., Jigyasu, R., Sharma, A., Mathew, L.: Review of various artificial intelligence techniques and its applications. IOP Conf. Ser. Mater. Sci. Eng. 594(1) (2019)Cheng, L., Yu, T.: A new generation of AI: a review and perspective on machine learning technologies applied to smart energy and electric power systems. Int. J. Energy Res. 43, 1928–1973 (2019)Seuring, S., Müller, M.: From a literature review to a conceptual framework for sustainable supply chain management. J. Clean. Prod. 16(15), 1699–1710 (2008). https://doi.org/10.1016/j.jclepro.2008.04.020Metaxiotis, K.S., Askounis, D., Psarras, J.: Expert Systems In Production Planning And Scheduling: A State-Of-The-Art Survey. J. Intell. Manuf. 13(4), 253–260 (2002). https://doi.org/10.1023/A:1016064126976Power, Y., Bahri, P.A.: Integration techniques in intelligent operational management: a review. Knowl. Based Syst. 18(2–3), 89–97 (2005). https://doi.org/10.1016/j.knosys.2004.04.009Shen, W., Hao, Q., Yoon, H.J., Norrie, D.H.: Applications of agent-based systems in intelligent manufacturing: an updated review. Adv. Eng. Inform. 20(4), 415–431 (2006). https://doi.org/10.1016/j.aei.2006.05.004Kobbacy, K.A.H., Vadera, S., Rasmy, M.H.: AI and OR in management of operations: history and trends. J. Oper. Res. Soc. 58(1), 10–28 (2007). https://doi.org/10.1057/palgrave.jors.2602132Zhang, W.J., Xie, S.Q.: Agent technology for collaborative process planning: a review. Int. J. Adv. Manuf. Technol. 32(3), 315–325 (2007). https://doi.org/10.1007/s00170-005-0345-xIbáñez, O., Cordón, O., Damas, S., Magdalena, L.: A review on the application of hybrid artificial intelligence systems to optimization problems in operations management. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds.) HAIS 2009. LNCS (LNAI), vol. 5572, pp. 360–367. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02319-4_43Kobbacy, K.A.H., Vadera, S.: A survey of AI in operations management from 2005 to 2009. J. Manuf. Technol. Manag. 22(6), 706–733 (2011). https://doi.org/10.1108/17410381111149602Guo, Z.X., Wong, W.K., Leung, S.Y.S., Li, M.: Applications of artificial intelligence in the apparel industry: a review. Text. Res. J. 81(18), 1871–1892 (2011). https://doi.org/10.1177/0040517511411968Priore, P., Gómez, A., Pino, R., Rosillo, R.: Dynamic scheduling of manufacturing systems using machine learning: an updated review. Artif. Intell. Eng. Des. Anal. Manuf. AIEDAM 28(1), 83–97 (2014). https://doi.org/10.1017/S0890060413000516Renzi, C., Leali, F., Cavazzuti, M., Andrisano, A.: A review on artificial intelligence applications to the optimal design of dedicated and reconfigurable manufacturing systems. Int. J. Adv. Manuf. Technol. 72(1–4), 403–418 (2014). https://doi.org/10.1007/s00170-014-5674-1Ngai, E.W.T., Peng, S., Alexander, P., Moon, K.K.L.: Decision support and intelligent systems in the textile and apparel supply chain: an academic review of research articles. Expert Syst. Appl. 41(1), 81–91 (2014). https://doi.org/10.1016/j.eswa.2013.07.013Rooh, U.A., Li, A., Ali, M.M.: Fuzzy, neural network and expert systems methodologies and applications - a review. J. Mob. Multimedia 11, 157–176 (2015)Bello, O., Teodoriu, C., Yaqoob, T., Oppelt, J., Holzmann, J., Obiwanne, A.: Application of artificial intelligence techniques in drilling system design and operations: a state of the art review and future research pathways. In: Society of Petroleum Engineers - SPE Nigeria Annual International Conference and Exhibition (2016)Arvitrida, N.I.: A review of agent-based modeling approach in the supply chain collaboration context. IOP Conf. Ser. Mater. Sci. Eng. 337(1) (2018). https://doi.org/10.1088/1757-899x/337/1/012015Zanon, L.G., Carpinetti, L.C.R.: Fuzzy cognitive maps and grey systems theory in the supply chain management context: a literature review and a research proposal. In: IEEE International Conference on Fuzzy Systems, July 2018, pp. 1–8 (2018). https://doi.org/10.1109/fuzz-ieee.2018.8491473Burggräf, P., Wagner, J., Koke, B.: Artificial intelligence in production management: a review of the current state of affairs and research trends in academia. In: 2018 International Conference on Information Management and Processing, ICIMP 2018, January 2018, pp. 82–88 (2018). https://doi.org/10.1109/icimp1.2018.8325846Diez-Olivan, A., Del Ser, J., Galar, D., Sierra, B.: Data fusion and machine learning for industrial prognosis: trends and perspectives towards Industry 4.0. Inf. Fusion 50, 92–111 (2019). https://doi.org/10.1016/j.inffus.2018.10.005Ni, D., Xiao, Z., Lim, M.K.: A systematic review of the research trends of machine learning in supply chain management. Int. J. Mach. Learn. Cybernet. 11(7), 1463–1482 (2019). https://doi.org/10.1007/s13042-019-01050-0Ning, C., You, F.: Optimization under uncertainty in the era of big data and deep learning: when machine learning meets mathematical programming. Comput. Chem. Eng. 125, 434–448 (2019). https://doi.org/10.1016/j.compchemeng.2019.03.034Okwu, M.O., Nwachukwu, A.N.: A review of fuzzy logic applications in petroleum exploration, production and distribution operations. J. Petrol. Explor. Prod. Technol. 9(2), 1555–1568 (2018). https://doi.org/10.1007/s13202-018-0560-2Weber, F.D., Schütte, R.: State-of-the-art and adoption of artificial intelligence in retailing. Digit. Policy Regul. Gov. 21(3), 264–279 (2019). https://doi.org/10.1108/DPRG-09-2018-0050Giri, C., Jain, S., Zeng, X., Bruniaux, P.: A detailed review of artificial intelligence applied in the fashion and apparel industry. IEEE Access 7, 95376–95396 (2019). https://doi.org/10.1109/ACCESS.2019.2928979Leo Kumar, S.P.: Knowledge-based expert system in manufacturing planning: State-of-the-art review. Int. J. Prod. Res. 57(15–16), 4766–4790 (2019). https://doi.org/10.1080/00207543.2018.1424372Barua, L., Zou, B., Zhou, Y.: Machine learning for international freight transportation management: a comprehensive review. Res. Transp. Bus. Manag. (2020). https://doi.org/10.1016/j.rtbm.2020.100453Chai, J., Ngai, E.W.T.: Decision-making techniques in supplier selection: recent accomplishments and what lies ahead. Expert Syst. Appl. 140 (2020). https://doi.org/10.1016/j.eswa.2019.112903Usuga Cadavid, J.P., Lamouri, S., Grabot, B., Pellerin, R., Fortin, A.: Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0. J. Intell. Manuf. 31(6), 1531–1558 (2020). https://doi.org/10.1007/s10845-019-01531-7Ekramifard, A., Amintoosi, H., Seno, A.H., Dehghantanha, A., Parizi, R.M.: A systematic literature review of integration of blockchain and artificial intelligence. In: Choo, K.-K.R., Dehghantanha, A., Parizi, R.M. (eds.) Blockchain Cybersecurity, Trust and Privacy. AIS, vol. 79, pp. 147–160. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-38181-3_8Vrbka, J., Rowland, Z.: Using artificial intelligence in company management. In: Ashmarina, S.I., Vochozka, M., Mantulenko, V.V. (eds.) ISCDTE 2019. LNNS, vol. 84, pp. 422–429. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-27015-5_51Leslie, D.: Understanding artificial intelligence ethics and safety: a guide for the responsible design and implementation of AI systems in the public sector. The Alan Turing Institute (2019)Queiroz, M.M., Ivanov, D., Dolgui, A., et al.: Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Ann Oper Res (2020). https://doi.org/10.1007/s10479-020-03685-

    A study of data-driven momentum and disposition effects in the Chinese stock market by functional data analysis

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    We apply a functional data analysis approach to decompose the cross-sectional Fama–French three-factor model residuals in the Chinese stock market. Our results indicate that other than Fama–French three factors, there are two orthonormal asset pricing factors describing the behavioral biases in their historical performances: between winner and loser stocks, and extreme and mediocre-performing stocks, respectively. We explain these two factors through investors’ overreaction, overconfidence and the lead-lag effect. These findings empirically show the existence of momentum and disposition effects in the Chinese stock market. A buy-and-hold mean-variance optimized portfolio incorporating these two market anomalies boosts the Sharpe ratio to 1.27

    Oroxylin A promotes PTEN-mediated negative regulation of MDM2 transcription via SIRT3-mediated deacetylation to stabilize p53 and inhibit glycolysis in wt-p53 cancer cells

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    Introduction p53 plays important roles in regulating the metabolic reprogramming of cancer, such as aerobic glycolysis. Oroxylin A is a natural active flavonoid with strong anticancer effects both in vitro and in vivo. Methods wt-p53 (MCF-7 and HCT116 cells) cancer cells and p53-null H1299 cancer cells were used. The glucose uptake and lactate production were analyzed using Lactic Acid production Detection kit and the Amplex Red Glucose Assay Kit. Then, the protein levels and RNA levels of p53, mouse double minute 2 (MDM2), and p53-targeted glycolytic enzymes were quantified using Western blotting and quantitative polymerase chain reaction (PCR), respectively. Immunoprecipitation were performed to assess the binding between p53, MDM2, and sirtuin-3 (SIRT3), and the deacetylation of phosphatase and tensin homolog (PTEN). Reporter assays were performed to assess the transcriptional activity of PTEN. In vivo, effects of oroxylin A was investigated in nude mice xenograft tumor-inoculated MCF-7 or HCT116 cells. Results Here, we analyzed the underlying mechanisms that oroxylin A regulated p53 level and glycolytic metabolism in wt-p53 cancer cells, and found that oroxylin A inhibited glycolysis through upregulating p53 level. Oroxylin A did not directly affect the transcription of wt-p53, but suppressed the MDM2-mediated degradation of p53 via downregulating MDM2 transcription in wt-p53 cancer cells. In further studies, we found that oroxylin A induced a reduction in MDM2 transcription by promoting the lipid phosphatase activity of phosphatase and tensin homolog, which was upregulated via sirtuin3-mediated deacetylation. In vivo, oroxylin A inhibited the tumor growth of nude mice-inoculated MCF-7 or HCT116 cells. The expression of MDM2 protein in tumor tissue was downregulated by oroxylin A as well. Conclusions These results provide a p53-independent mechanism of MDM2 transcription and reveal the potential of oroxylin A on glycolytic regulation in both wt-p53 and mut-p53 cancer cells. The studies have important implications for the investigation on anticancer effects of oroxylin A, and provide the academic basis for the clinical trial of oroxylin A in cancer patients

    Skp is a multivalent chaperone of outer membrane proteins

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    The trimeric chaperone Skp sequesters outer-membrane proteins (OMPs) within a hydrophobic cage, thereby preventing their aggregation during transport across the periplasm in Gram-negative bacteria. Here, we studied the interaction between Escherichia coli Skp and five OMPs of varying size. Investigations of the kinetics of OMP folding revealed that higher Skp/OMP ratios are required to prevent the folding of 16-stranded OMPs compared with their 8-stranded counterparts. Ion mobility spectrometry–mass spectrometry (IMS–MS) data, computer modeling and molecular dynamics simulations provided evidence that 10- to 16-stranded OMPs are encapsulated within an expanded Skp substrate cage. For OMPs that cannot be fully accommodated in the expanded cavity, sequestration is achieved by binding of an additional Skp trimer. The results suggest a new mechanism for Skp chaperone activity involving the coordination of multiple copies of Skp in protecting a single substrate from aggregation

    Abortive Autophagy Induces Endoplasmic Reticulum Stress and Cell Death in Cancer Cells

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    Autophagic cell death or abortive autophagy has been proposed to eliminate damaged as well as cancer cells, but there remains a critical gap in our knowledge in how this process is regulated. The goal of this study was to identify modulators of the autophagic cell death pathway and elucidate their effects on cellular signaling and function. The result of our siRNA library screenings show that an intact coatomer complex I (COPI) is obligatory for productive autophagy. Depletion of COPI complex members decreased cell survival and impaired productive autophagy which preceded endoplasmic reticulum stress. Further, abortive autophagy provoked by COPI depletion significantly altered growth factor signaling in multiple cancer cell lines. Finally, we show that COPI complex members are overexpressed in an array of cancer cell lines and several types of cancer tissues as compared to normal cell lines or tissues. In cancer tissues, overexpression of COPI members is associated with poor prognosis. Our results demonstrate that the coatomer complex is essential for productive autophagy and cellular survival, and thus inhibition of COPI members may promote cell death of cancer cells when apoptosis is compromised
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