| 1. |
- Asif, Muhammad H., et al.
(författare)
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ZnO Nanostructure-Based Intracellular Sensor
- 2015
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 15:5, s. 11787-11804
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Forskningsöversikt (refereegranskat)abstract
- Recently ZnO has attracted much interest because of its usefulness for intracellular measurements of biochemical species by using its semiconducting, electrochemical, catalytic properties and for being biosafe and biocompatible. ZnO thus has a wide range of applications in optoelectronics, intracellular nanosensors, transducers, energy conversion and medical sciences. This review relates specifically to intracellular electrochemical (glucose and free metal ion) biosensors based on functionalized zinc oxide nanowires/nanorods. For intracellular measurements, the ZnO nanowires/nanorods were grown on the tip of a borosilicate glass capillary (0.7 mu m in diameter) and functionalized with membranes or enzymes to produce intracellular selective metal ion or glucose sensors. Successful intracellular measurements were carried out using ZnO nanowires/nanorods grown on small tips for glucose and free metal ions using two types of cells, human fat cells and frog oocytes. The sensors in this study were used to detect real-time changes of metal ions and glucose across human fat cells and frog cells using changes in the electrochemical potential at the interface of the intracellular micro-environment. Such devices are helpful in explaining various intracellular processes involving ions and glucose.
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| 2. |
- Danielsson, Bengt, et al.
(författare)
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Antidepressants and antipsychotics classified with torsades de pointes arrhythmia risk and mortality in older adults - a Swedish nationwide study
- 2016
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 81:4, s. 773-783
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Tidskriftsartikel (refereegranskat)abstract
- AimThe aim of the study was to examine mortality risk associated with use of antidepressants and antipsychotics classified with torsades de pointes (TdP) risk in elderly. MethodsA matched case-control register study was conducted in people 65 years and older dying outside hospital from 2008-2013 (n=286092) and matched controls (n=1430460). The association between prescription of antidepressants and antipsychotics with various TdP risk according to CredibleMeds () and all-cause mortality was studied by multivariate conditional logistic regression adjusted for comorbidity and several other confounders. ResultsUse of antidepressants classified with known or possible TdP risk, was associated with higher adjusted risk for mortality (OR 1.53, 95% CI 1.51, 1.56 and OR 1.63, 95% CI 1.61, 1.67, respectively) compared with antidepressants classified with conditional TdP risk (OR 1.25, 95% CI 1.22, 1.28) or without TdP classification (OR 0.99, 95% CI 0.94, 1.05). Antipsychotics classified with known TdP risk were associated with higher risk (OR 4.57, 95% CI 4.37, 4.78) than antipsychotics with possible risk (OR 2.58, 95% CI 2.52, 2.64) or without TdP classification (OR 2.14, 95% CI 2.03, 2.65). The following risk ranking was observed for commonly used antidepressants: mirtazapine > citalopram > sertraline > amitriptyline and for antipsychotics: haloperidol > risperidone >olanzapine > quetiapine. ConclusionThe CredibleMeds system predicted drug-associated risk for mortality in the elderly at the risk class level. Among antipsychotics, haloperidol, and among antidepressants, mirtazapine and citalopram, were associated with the highest risks. The results suggest that the TdP risk with antidepressants and antipsychotics should be taken into consideration when prescribing to the elderly.
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| 3. |
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| 4. |
- Glorieux, Emile, 1989-, et al.
(författare)
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Constructive cooperative coevolution for large-scale global optimisation
- 2017
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Ingår i: Journal of Heuristics. - : Springer Science and Business Media LLC. - 1381-1231 .- 1572-9397. ; 23:6, s. 449-469
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents the Constructive Cooperative Coevolutionary ( C3C3 ) algorithm, applied to continuous large-scale global optimisation problems. The novelty of C3C3 is that it utilises a multi-start architecture and incorporates the Cooperative Coevolutionary algorithm. The considered optimisation problem is decomposed into subproblems. An embedded optimisation algorithm optimises the subproblems separately while exchanging information to co-adapt the solutions for the subproblems. Further, C3C3 includes a novel constructive heuristic that generates different feasible solutions for the entire problem and thereby expedites the search. In this work, two different versions of C3C3 are evaluated on high-dimensional benchmark problems, including the CEC'2013 test suite for large-scale global optimisation. C3C3 is compared with several state-of-the-art algorithms, which shows that C3C3 is among the most competitive algorithms. C3C3 outperforms the other algorithms for most partially separable functions and overlapping functions. This shows that C3C3 is an effective algorithm for large-scale global optimisation. This paper demonstrates the enhanced performance by using constructive heuristics for generating initial feasible solutions for Cooperative Coevolutionary algorithms in a multi-start framework.
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| 5. |
- Glorieux, Emile
(författare)
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Constructive cooperative coevolution for optimising interacting production stations
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Engineering problems have characteristics such as a large number of variables, non-linear, computationally expensive, complex and black-box (i.e. unknown internal structure). These characteristics prompt difficulties for existing optimisation techniques. A consequence of this is that the required optimisation time rapidly increases beyond what is practical. There is a needfor dedicated techniques to exploit the power of mathematical optimisation tosolve engineering problems. The objective of this thesis is to investigate thisneed within the field of automation, specifically for control optimisation ofautomated systems.The thesis proposes an optimisation algorithm for optimising the controlof automated interacting production stations (i.e. independent stations thatinteract by for example material handling robots). The objective of the optimisation is to increase the production rate of such systems. The non-separable nature of these problems due to the interactions, makes them hard to optimise.The proposed algorithm is called the Constructive Cooperative CoevolutionAlgorithm (C3). The thesis presents the experimental evaluation of C3, bothon theoretical and real-world problems. For the theoretical problems, C3 istested on a set of standard benchmark functions. The performance, robustness and convergence speed of C3 is compared with the algorithms. This shows that C3 is a competitive optimisation algorithm for large-scale non-separable problems.C3 is also evaluated on real-world industrial problems, concerning thecontrol of interacting production stations, and compared with other optimisation algorithms on these problems. This shows that C3 is very well-suited for these problems. The importance of considering the energy consumption and equipment wear, next to the production rate, in the objective function is also investigated. This shows that it is crucial that these are considered to optimise the overall performance of interacting production stations.
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| 6. |
- Glorieux, Emile, 1989-, et al.
(författare)
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Constructive cooperative coevolutionary optimisation for interacting production stations
- 2015
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Ingår i: The International Journal of Advanced Manufacturing Technology. - : Springer Science and Business Media LLC. - 0268-3768 .- 1433-3015. ; 78:1-4, s. 673-688
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Tidskriftsartikel (refereegranskat)abstract
- Optimisation of the control function for multiple automated interacting production stations is a complex problem, even for skilled and experienced operators or process planners. When using mathematical optimisation techniques, it often becomes necessary to use simulation models to represent the problem because of the high complexity (i.e. simulation-based optimisation). Standard optimisation techniques are likely to either exceed the practical time frame or under-perform compared to the manual tuning by the operators or process planners. This paper presents the Constructive cooperative coevolutionary (C3) algorithm, which objective is to enable effective simulation-based optimisation for the control of automated interacting production stations within a practical time frame. C3 is inspired by an existing cooperative coevolutionary algorithm. Thereby, it embeds an algorithm that optimises subproblems separately. C3 also incorporates a novel constructive heuristic to find good initial solutions and thereby expedite the optimisation. In this work, two industrial optimisation problems, involving interaction production stations, with different sizes are used to evaluate C3. The results illustrate that with C3, it is possible to optimise these problems within a practical time frame and obtain a better solution compared to manual tuning.
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| 7. |
- Glorieux, Emile, et al.
(författare)
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Improved Constructive Cooperative Coevolutionary Differential Evolution for Large-Scale Optimisation
- 2016
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Ingår i: Computational Intelligence, 2015 IEEE Symposium Series on. - : IEEE. - 9781479975600 ; , s. 1703-1710
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Konferensbidrag (refereegranskat)abstract
- The Differential Evolution (DE) algorithm is widely used for real-world global optimisation problems in many different domains. To improve DE's performance on large-scale optimisation problems, it has been combined with the Cooperative Coevolution (CCDE) algorithm. CCDE adopts a divide-and-conquer strategy to optimise smaller subcomponents separately instead of tackling the large-scale problem at once. DE then evolves a separate subpopulation for each subcomponent but there is cooperation between the subpopulations to co-adapt the individuals of the subpopulations with each other. The Constructive Cooperative Coevolution (C3DE) algorithm, previously proposed by the authors, is an extended version of CCDE that has a better performance on large-scale problems, interestingly also on non-separable problems. This paper proposes a new version, called the Improved Constructive Cooperative Coevolutionary Differential Evolution (C3iDE), which removes several limitations with the previous version. A novel element of C3iDE is the advanced initialisation of the subpopulations. C3iDE initially optimises the subpopulations in a partially co-adaptive fashion. During the initial optimisation of a subpopulation, only a subset of the other subcomponents is considered for the co-adaptation. This subset increases stepwise until all subcomponents are considered. The experimental evaluation of C3iDE on 36 high-dimensional benchmark functions (up to 1000 dimensions) shows an improved solution quality on large-scale global optimisation problems compared to CCDE and DE. The greediness of the co-adaptation with C3iDE is also investigated in this paper.
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| 8. |
- Glorieux, E., et al.
(författare)
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Improved Constructive Cooperative Coevolutionary Differential Evolution for Large-Scale Optimisation
- 2015
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Ingår i: Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015. - : IEEE. - 9781479975600 ; , s. 1703-1710
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Konferensbidrag (refereegranskat)abstract
- The Differential Evolution (DE) algorithm is widely used for real-world global optimisation problems in many different domains. To improve DE's performance on large-scale optimisation problems, it has been combined with the Cooperative Coevolution (CCDE) algorithm. CCDE adopts a divide-and-conquer strategy to optimise smaller subcomponents separately instead of tackling the large-scale problem at once. DE then evolves a separate subpopulation for each subcomponent but there is cooperation between the subpopulations to co-adapt the individuals of the subpopulations with each other. The Constructive Cooperative Coevolution ((CDE)-D-3) algorithm, previously proposed by the authors, is an extended version of CCDE that has a better performance on large-scale problems, interestingly also on non-separable problems. This paper proposes a new version, called the Improved Constructive Cooperative Coevolutionary Differential Evolution ((CDE)-D-3i), which removes several limitations with the previous version. A novel element of (CDE)-D-3i is the advanced initialisation of the subpopulations. (CDE)-D-3i initially optimises the subpopulations in a partially co-adaptive fashion. During the initial optimisation of a subpopulation, only a subset of the other subcomponents is considered for the co-adaptation. This subset increases stepwise until all subcomponents are considered. The experimental evaluation of (CDE)-D-3i on 36 high-dimensional benchmark functions (up to 1000 dimensions) shows an improved solution quality on large-scale global optimisation problems compared to CCDE and DE. The greediness of the co-adaptation with (CDE)-D-3i is also investigated in this paper.
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| 9. |
- Glorieux, Emile, 1989-, et al.
(författare)
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Multi-objective constructive cooperative coevolutionary optimization of robotic press-line tending
- 2017
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Ingår i: Engineering optimization (Print). - 0305-215X .- 1029-0273. ; 49:10, s. 1685-1703
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Tidskriftsartikel (refereegranskat)abstract
- This article investigates multi-objective optimization of the robot trajectories and position-based operation-coordination of complex multi-robot systems, such as press lines, to improve the production rate and obtaining smooth motions to avoid excessive wear of the robots’ components. Different functions for handling the multiple objectives are evaluated on realworld press lines, including both scalarizing single-objective functions and Pareto-based multi-objective functions. Additionally, the Multi-Objective Constructive Cooperative Coevolutionary (moC3) algorithm is proposed, for Pareto-based optimization, which uses a novel constructive initialization of the subpopulations in a co-adaptive fashion. It was found that Paretobased optimization performs better than the scalarizing single-objective functions. Furthermore, moC3 gives substantially better results compared to manual online tuning, as currently used in the industry. Optimizing robot trajectories and operation-coordination of complex multi-robot systems using the proposed method with moC3 significantly improves productivity and reduces maintenance. This article hereby addresses the lack of systematic methods for effectively improving the productivity of press lines.
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| 10. |
- Glorieux, E., et al.
(författare)
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Multi-objective constructive cooperative coevolutionary optimization of robotic press-line tending
- 2017
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Ingår i: Engineering Optimization. - : Informa UK Limited. - 1029-0273 .- 0305-215X. ; 49:10, s. 1685-1703
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Tidskriftsartikel (refereegranskat)abstract
- This article investigates multi-objective optimization of the robot trajectories and position-based operation-coordination of complex multi-robot systems, such as press lines, to improve the production rate and obtaining smooth motions to avoid excessive wear of the robots' components. Different functions for handling the multiple objectives are evaluated on real-world press lines, including both scalarizing single-objective functions and Pareto-based multi-objective functions. Additionally, the Multi-Objective Constructive Cooperative Coevolutionary (moC(3)) algorithm is proposed, for Pareto-based optimization, which uses a novel constructive initialization of the subpopulations in a co-adaptive fashion. It was found that Pareto-based optimization performs better than the scalarizing single-objective functions. Furthermore, C-mo(3) gives substantially better results compared to manual online tuning, as currently used in the industry. Optimizing robot trajectories and operation-coordination of complex multi-robot systems using the proposed method with C-mo(3) significantly improves productivity and reduces maintenance. This article hereby addresses the lack of systematic methods for effectively improving the productivity of press lines.
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