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- Albaqami, Munirah D., et al.
(författare)
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The fast nucleation/growth of Co3O4 nanowires on cotton silk : the facile development of a potentiometric uric acid biosensor
- 2022
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Ingår i: RSC Advances. - : Royal Society of Chemistry. - 2046-2069. ; 12:29, s. 18321-18332
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Tidskriftsartikel (refereegranskat)abstract
- In this study, we have used cotton silk as a source of abundant hydroxyl groups for the fast nucleation/growth of cobalt oxide (Co3O4) nanowires via a hydrothermal method. The crystal planes of the Co3O4 nanowires well matched the cubic phase. The as-synthesized Co3O4 nanowires mainly contained cobalt and oxygen elements and were found to be highly sensitive towards uric acid in 0.01 M phosphate buffer solution at pH 7.4. Importantly, the Co3O4 nanowires exhibited a large surface area, which was heavily utilized during the immobilization of the enzyme uricase via a physical adsorption method. The potentiometric response of the uricase-immobilizing Co3O4 nanowires was measured in the presence of uric acid (UA) against a silver/silver chloride (Ag/AgCl) reference electrode. The newly fabricated uric acid biosensor possessed a low limit of detection of 1.0 +/- 0.2 nM with a wide linear range of 5 nM to 10 mM and sensitivity of 30.6 mV dec(-1). Additionally, several related parameters of the developed uric acid biosensor were investigated, such as the repeatability, reproducibility, storage stability, selectivity, and dynamic response time, and these were found to be satisfactory. The good performance of the Co3O4 nanowires was verified based on the fast charge-transfer kinetics, as confirmed via electrochemical impedance spectroscopy. The successful practical use of the uric acid biosensor was demonstrated based on the recovery method. The observed performance of the uricase-immobilizing Co3O4 nanowires revealed that they could be considered as a promising and alternative tool for the detection of uric acid under both in vitro and in vivo conditions. Also, the use of cotton silk as a source of abundant hydroxyl groups may be considered for the remarkably fast nucleation/growth of other metal-oxide nanostructures, thereby facilitating the fabrication of functional electrochemical devices, such as batteries, water-splitting devices, and supercapacitors.
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| 14. |
- Alshgari, Razan A., et al.
(författare)
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Manipulation of CuO morphology for efficient potentiometric detection of urea via slow nucleation/growth kinetics exerted by mixed solvents
- 2022
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Ingår i: Journal of materials science. Materials in electronics. - : SPRINGER. - 0957-4522 .- 1573-482X. ; 33, s. 25250-25262
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Tidskriftsartikel (refereegranskat)abstract
- Controlling the reaction kinetics during the nucleation/growth of cupric oxide (CuO) nanostructures is very critical in order to achieve a specific and well-defined morphology. For this purpose, we have slowed down the reaction speed using a mixed solvent concept and successfully obtained a chain-like morphology of CuO nanostructures using hydrothermal method. The CuO chain-like morphology was synthesized using a 1:1 (v/v) ratio of ethylene glycol and water. The morphology and crystalline features of CuO were studied by scanning electron microscopy (SEM) and powder X-ray diffraction techniques. The high resolution transmission electron microscopy revealed 5 nm crystallite size for the CuO material prepared in the mixed solvents. The obtained results have shown that the prepared CuO chains had a monocline phase, containing only Cu and O as main elements as confirmed by energy dispersive spectroscopy. This unique morphology obtained from mixed solvent process has provided a better surface for the loading of urease enzyme, thus it enabled the development of sensitive and selective urea biosensor in phosphate buffer solution of pH 7.4. The physical adsorption method was used to immobilize urease enzyme onto the nano surface of CuO. The fabricated biosensor based on urease/CuO chains has shown a dynamic linear range from 0.0005 to15 mM with a low limit of detection 0.0001 mM. Additionally, a fast response time aroudn1s, h high selectivity, stability, repeatability, storage time, and reproducibility were observed. The effect of pH and temperature on the potentiometric signal of the developed biosensor was also examined. Importantly, the practical aspects of the fabricated urea biosensor were probed and the obtained percent recovery results revealed an outstanding performance. The strategy of using mixed solvent with equal volume ratio would be useful for the preparation of other metal oxides with improved catalytic properties for a wide range of clinical, biomedical and other related applications.
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| 15. |
- Djehiche, Boualem, 1962-, et al.
(författare)
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Non asymptotic estimation lower bounds forLTI state space models with Cramér-Rao and van Trees
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We study the estimation problem for linear time-invariant (LTI) state-space models with Gaussian excitation of an unknown covariance. We provide non asymptotic lower bounds for the expected estimation error and the mean square estimation risk of the least square estimator, and the minimax mean square estimation risk. These bounds are sharp with explicit constants when the matrix of the dynamics has no eigenvalues on the unit circle and are rate-optimal when they do. Our results extend and improve existing lower bounds to lower bounds in expectation of the mean square estimation risk and to systems with a general noise covariance. Instrumental to our derivation are new concentration results for rescaled sample covariances and deviation results for the corresponding multiplication processes of the covariates, a differential geometric construction of a prior on the unit operator ball of small Fisher information, and an extension of the Cramér-Rao and van Treesinequalities to matrix-valued estimators.
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| 16. |
- Lamb, Alastair D, et al.
(författare)
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Aiming for a holistic integrated service for men diagnosed with prostate cancer – Definitions of standards and skill sets for nurses and allied healthcare professionals
- 2017
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Ingår i: European Journal of Oncology Nursing. - : Elsevier BV. - 1462-3889. ; 29, s. 31-38
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Tidskriftsartikel (refereegranskat)abstract
- Purpose To establish a comprehensive set of recommendations for the service structure and skill set of nurses and allied healthcare professionals in prostate cancer care. Methods Using components of formal consensus methodology, a 30-member multidisciplinary panel produced 53 items for discussion relating to the provision of care for prostate cancer patients by specialist nurses and allied healthcare professionals. Items were developed by two rounds of email correspondence in which, first, items were generated and, second, items refined to form the basis of a consensus meeting which constituted the third round of review. The fourth and final round was an email review of the consensus output. Results The panel agreed on 33 items that were appropriate for recommendations to be made. These items were grouped under categories of “Environment” and “Patient Pathway” and included comments on training, leadership, communication and quality assessment as well as specific items related to prostate diagnosis clinics, radical treatment clinics and follow-up survivor groups. Conclusions Specialist nurses and allied healthcare professionals play a vital role alongside urologists and oncologists to provide care to men with prostate cancer and their families. We present a set of standards and consensus recommendations for the roles and skill-set required for these practitioners to provide gold-standard prostate cancer care. These recommendations could form the basis for development of comprehensive integrated prostate cancer pathways in prostate cancer centres as well as providing guidance for any units treating men with prostate cancer.
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| 17. |
- Mazhar, Othmane, Ph.D. student, 1990-
(författare)
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Data driven modeling in the presence of time series structure: : Improved bounds and effective algorithms
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis consists of five appended papers devoted to modeling tasks where the desired models are learned from data sets with an underlying time series structure. We develop a statistical methodology for providing efficient estimators and analyzing their non-asymptotic behavior. We further suggest novel algorithmic design techniques for obtaining practical procedures to compute these estimators. Specifically, we study time series models of increasing levels of difficulty. In the first paper, we study change point and clustering systems where the dynamic structure of the time series is entirely encoded in the combinatorial properties of the estimated parameters. We then investigate in the second paper Finite Input Response (FIR) models, which exhibit a time-shifted random design. The obtained results are then generalized in the third paper to linear Hidden Markov models since they are infinite impulse response models with a particular polynomial structure. Finally, in the fourth and fifth papers, we investigate linear time-invariant (LTI) state-space models where the covariates generated along the path of the system are not just dependent but also dependent on the estimated parameter. Hence, the spectral properties of this estimated parameter affect the estimation performance. Throughout this journey, we develop a statistical methodology for deriving statistically efficient estimators. This statistical methodology relays on the idea that efficient estimators should strike a compromise between a signal term and a noise term. The signal term is intimately related to the spectral properties of the design matrix, and the noise term is intimately associated with the covariates multiplication process. To quantify both of these terms and obtain upper bounds for the estimation errors, we develop new concentration and deviation inequalities based on chaining integrals and self-normalized martingale inequalities. We also obtain lower bounds for the estimation errors by extending the Cramér-Rao inequality to a biased estimator and alow-rank Fisher information and provide an information geometric construction of carefully chosen priors on sets of matrices to obtain a van Tree inequality describing the minimax rate for the estimation problem. Finally, on the algorithmic side, we design efficient estimation procedures based on dynamic programming, penalized least squares, and the Ho-Kalman algorithm to take into account the data’s time series structure.
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| 18. |
- Shi, Shengling, et al.
(författare)
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Finite-Sample Analysis of Identification of Switched Linear Systems With Arbitrary or Restricted Switching
- 2022
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Ingår i: IEEE Control Systems Letters. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2475-1456. ; 7, s. 121-126
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Tidskriftsartikel (refereegranskat)abstract
- For the identification of switched systems with measured states and a measured switching signal, this letter aims to analyze the effect of switching strategies on the estimation error. The data is assumed to be collected from globally asymptotically or marginally stable switched systems under switches that are arbitrary or subject to an average dwell time constraint. Then the switched system is estimated by the least-squares (LS) estimator. To capture the effect of the parameters of the switching strategies on the LS estimation error, finite-sample error bounds are developed in this letter. The obtained error bounds show that the estimation error is logarithmic of the switching parameters when there are only stable modes; however, when there are unstable modes, the estimation error bound can increase linearly as the switching parameter changes. This suggests that in the presence of unstable modes, the switching strategy should be properly designed to avoid the significant increase of the estimation error.
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