| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
- Lin, Di, et al.
(författare)
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Neural Networks for Computer-Aided Diagnosis in Medicine : a review
- 2016
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Ingår i: Neurocomputing. - : Elsevier BV. - 0925-2312 .- 1872-8286. ; 216, s. 700-708
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Tidskriftsartikel (refereegranskat)abstract
- This survey makes an overview of the most recent applications on the neural networks for the computer-aided medical diagnosis (CAMD) over the past decade. CAMD can facilitate the automation of decision making, extraction and visualization of complex characteristics for clinical diagnosis purposes. Over the past decade, neural networks have attained considerable research interest and are widely employed to complex CAMD systems in diverse clinical application domains, such as detecting diseases, classification of diseases, testing the compatibility of new drugs, etc. Overall, this paper reviews the state-of-the-art of neural networks for CAMD. It helps the readers understand the topic of neural networks for CAMD by summarizing the findings addressed in recent academic papers as well as presenting a few open issues of developing the research on this topic.
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| 3. |
- Lin, Di, et al.
(författare)
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Optimal Network QoS over the Internet of Vehicles for E-Health Applications
- 2016
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Ingår i: International Journal of Mobile Information Systems. - : Hindawi Limited. - 1574-017X .- 1875-905X. ; 2016
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Tidskriftsartikel (refereegranskat)abstract
- Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In consideration of EMI on medical sensors, we study the optimization of quality of service (QoS) within the whole Internet of vehicles for E-health and propose a novel model to optimize the QoS by allocating the transmit power of each user. Our results show that the optimal power control policy depends on the objective of optimization problems: a greedy policy is optimal to maximize the summation of QoS of each user, whereas a fair policy is optimal to maximize the product of QoS of each user. Algorithms are taken to derive the optimal policies, and numerical results of optimizing QoS are presented for both objectives and QoS constraints.
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| 4. |
- Lin, Di, et al.
(författare)
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User-priority based power control over the D2D assisted Internet of vehicles for mobile health
- 2017
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 4:3, s. 824-831
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Tidskriftsartikel (refereegranskat)abstract
- A device-to-device (D2D) assisted cellular network is pervasive to support ubiquitous healthcare applications, since it is expected to bring the significant benefits of improving user throughput, extending the battery life of mobiles, etc. However, D2D and cellular communications in the same network may cause cross-tier interference (CTI) to each other. Also a critical issue of using D2D assisted cellular networks under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical equipments. In consideration of CTI and EMI, we study the problem of optimizing individual channel rates of the mobile users in different priorities (different levels of emergency) within the Internet of vehicles for mobile health, and propose an algorithm of controlling the transmit power to solve the above-mentioned problem under a gametheoretical framework. Numerical results show that the proposed algorithm can converge linearly to the optimum, while ensuring an allowable level of EMI on medical equipments.
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