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  • 1
    In: Autophagy, Informa UK Limited, Vol. 17, No. 1 ( 2021-01-02), p. 1-382
    Type of Medium: Online Resource
    ISSN: 1554-8627 , 1554-8635
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2262043-6
    SSG: 12
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  • 2
    In: Database, Oxford University Press (OUP), Vol. 2019 ( 2019-01-01)
    Abstract: Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.
    Type of Medium: Online Resource
    ISSN: 1758-0463
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2496706-3
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  • 3
    In: Small, Wiley, Vol. 12, No. 11 ( 2016-03), p. 1506-1513
    Abstract: Theranostic nanomedicines that integrate diagnostic and therapeutic moieties into a single nanoscale platform are playing an increasingly important role in fighting cancer. Here, a facile and green synthetic strategy for hollow CoPt alloy nanoparticles (HCPA‐NPs) using plant polyphenols as assisted agents is reported for the first time. This novel strategy enables size‐controlled synthesis of HCPA‐NPs through the control of the molecular sizes of polyphenols. It is also a versatile strategy for synthesizing other hollow alloy nanoparticles with various metal compositions due to the diverse metal‐chelating ability of the polyphenols. Further studies show that HCPA‐NPs have good biocompatibility and can be successfully implemented for magnetic resonance and photoacoustic dual‐modal imaging guided photothermal therapy. This work brings new insights for the green synthesis of hollow nanoparticles and extends these biocompatible nanoparticles for theranostic applications.
    Type of Medium: Online Resource
    ISSN: 1613-6810 , 1613-6829
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 2168935-0
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  • 4
    In: Open Medicine Journal, Bentham Science Publishers Ltd., Vol. 10, No. 1 ( 2023-08-18)
    Abstract: We aimed to explore the risk factors for acute ischemic stroke-associated pneumonia (SAP) and evaluate the predictive value of the Age, Atrial fibrillation, Dysphagia, Sex, Stroke Severity (A2DS2) score, neutrophil-to-lymphocyte ratio (NLR), and a combination of both indices for acute ischemic SAP. Methods: Overall, 1,505 patients with acute ischemic stroke (AIS) were enrolled and divided into SAP and non-SAP groups. Patients’ age, sex, and medical history (alcohol consumption, hypertension, diabetes, hyperlipidemia, coronary disease, atrial fibrillation, chronic obstructive pulmonary disease, and stroke history) were recorded. Clinical data were recorded, including consciousness disturbance, dysphagia, indwelling nasogastric tube, thrombolytic therapy, hospital stay length, National Institute of Health Stroke Scale (NIHSS) score, stroke position, TOAST classification, and blood pressure on admission. Laboratory indicators, including white blood cell (WBC) count, neutrophil count, lymphocyte count, creatinine, homocysteine, and fasting blood glucose, were also recorded. NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. All patients were scored using A2DS2. Binary logistic regression was used to analyze the relationships between A2DS2, NLR, and SAP. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic value of A2DS2, NLR, and their combined indices for predicting SAP. Results: SAP occurred in 203 (13.5%) of the 1,505 enrolled patients. Patients in the SAP group were older and had a higher proportion of hypertension and chronic obstructive pulmonary disease history, consciousness disorder, dysphagia, indwelling nasogastric tube, fasting blood glucose level, NIHSS score, and longer hospital stay. The SAP group had a higher A2DS2 score than the non-SAP group. Similarly, the WBC count, neutrophil count, and NLR were significantly higher in the SAP group than in the non-SAP group. After excluding confounding factors, binary logistic regression analysis showed that age, NIHSS score, NLR, and A2DS2 score were independent risk factors for SAP. The ROC curves showed the A2DS2 score and NLR predicted SAP with an area under the curve (AUC) of 0.855 (sensitivity: 73.3%, specificity: 86.1%) and 0.849 (sensitivity: 79.7%, specificity: 80.6%), respectively, and the combined prediction of SAP AUC was 0.924 (sensitivity: 87.7%, specificity: 82.8%), which was higher than that of a single index, with improved the sensitivity of prediction. Conclusion: In patients with AIS, the A2DS2 score combined with NLR is of greater value in predicting the risk of acute ischemic SAP than a single indicator.
    Type of Medium: Online Resource
    ISSN: 1874-2203
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2023
    detail.hit.zdb_id: 2812929-5
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  • 5
    In: Processes, MDPI AG, Vol. 10, No. 12 ( 2022-12-15), p. 2714-
    Abstract: The existing research and practices have shown that the coordinated implementation of lean-green manufacturing can have a positive impact on the economic and environmental benefits, which is an effective means to ensure the environmental protection of the production process of manufacturing without damaging their profitability. Within the field of lean-green research, there is still a lack of research to analyze the driving factors for the collaborative implementation of integrated lean and green integration. Although, some scholars and researchers have studied lean and green integration paradigms, their research has mostly focused on lean-green integration practices and their impact on environmental performance and their respective operations. In the context of Industry 4.0, this article investigates the driving forces behind the collaborative integration implementation of a lean-green manufacturing system from the viewpoint of stakeholders. Specifically addressing the issues of correlation and ambiguity in the identification of driving factors, this manuscript proposes an Interpretation Structure Model (ISM) of fuzzy comprehensive Analytic Hierarchy Process (AHP), based on Decision-Making Trial and Evaluation Laboratory (DEMATEL), to determine the importance of the driving factors. Combined with the complex network theory, the evaluation index system is divided into four levels from eight factor categories, including endogenous lean-green driving factors and exogenous driving factors. The fuzzy AHP-DEMATEL-ISM is used to analyze the relationship between indicators and the structure of the indicator system. The complex network which is composed of the indicator system is divided into different levels. The importance of indicators is analyzed from the perspective of the global network, and key factors affecting the driving of lean-green system is analyzed. The integration of the lean-green manufacturing system and organizational synergy are promoted to jointly lead the enterprise toward sustainable development by paying particular attention to the primary impact indicators and aggressively cultivating the key impact indicators.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2720994-5
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  • 6
    In: Processes, MDPI AG, Vol. 11, No. 6 ( 2023-06-06), p. 1730-
    Abstract: In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A “time window span” was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of improving workstation service satisfaction. Lastly, in order to verify the effectiveness of the model and algorithm proposed in this study, a simulation experiment has been conducted on the workstation logistics distribution system in a smart manufacturing workshop to provide convincing evidence for optimizing workstation logistics distribution paths in workshops of discrete manufacturing enterprises.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2720994-5
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  • 7
    In: The American Journal of Emergency Medicine, Elsevier BV, Vol. 38, No. 10 ( 2020-10), p. 2101-2109
    Type of Medium: Online Resource
    ISSN: 0735-6757
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 2041648-9
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  • 8
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2012
    In:  Nature Communications Vol. 3, No. 1 ( 2012-11-06)
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2012-11-06)
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2012
    detail.hit.zdb_id: 2553671-0
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  • 9
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2014
    In:  Advances in Difference Equations Vol. 2014, No. 1 ( 2014-12)
    In: Advances in Difference Equations, Springer Science and Business Media LLC, Vol. 2014, No. 1 ( 2014-12)
    Abstract: In this paper, we study a class of stochastic neutral Volterra-Levin equations which are equipped with Lévy noise and variable delay and we obtain p th moment exponential stability. Some well-known results are improved and generalized.
    Type of Medium: Online Resource
    ISSN: 1687-1847
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2014
    detail.hit.zdb_id: 2132815-8
    detail.hit.zdb_id: 3112904-3
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  • 10
    In: Processes, MDPI AG, Vol. 11, No. 2 ( 2023-02-07), p. 499-
    Abstract: In the context of Industry 4.0, the lean–green manufacturing system has brought many advantages and challenges to industrial participants. Security is one of the main challenges encountered in the new industrial environment, because smart factory applications can easily expose the vulnerability of manufacturing and threaten the operational security of the whole system. It is difficult to address the problem of the brittleness factor in manufacturing systems. Therefore, building on vulnerability theory, this study proposes a vulnerability index system for lean–green manufacturing systems in a manufacturing company in the context of Industry 4.0. The index has four dimensions: human factors, equipment factors, environmental factors, and other factors. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was used to calculate the degree of influence, the degree of being influenced, and the centrality and causes of the factors. The causal relationships and key influences between the factors were identified. Then, the dependence and hierarchy of each of the key influencing factors were analyzed using the Matrix-Based Cross-Impact Multiplication Applied to Classification (MICMAC) and Interpretative Structural Model (ISM) methods, and a hierarchical structural model of the factors was constructed. Finally, an intelligent manufacturing system that produces a micro-acoustic material and device was used as an example to verify the accuracy of the proposed method. The results show that the method not only identifies the key brittleness factors in a lean–green manufacturing system but can also provide a guarantee for the safe operation of a manufacturing system. This study provides theoretical guidance for the effective management of intelligent manufacturing systems; moreover, it lays a foundation and provides a new methodology for assessing the vulnerability of manufacturing systems.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2720994-5
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