| 1. |
- Beal, Jacob, et al.
(author)
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Robust estimation of bacterial cell count from optical density
- 2020
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Journal article (peer-reviewed)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. |
- Fan, Zhiwen, et al.
(author)
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Porous Ionic Network/CNT Composite Separator as a Polysulfide Snaring Shield for High Performance Lithium–Sulfur Battery
- 2023
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In: Macromolecular rapid communications. - 1022-1336 .- 1521-3927. ; 44:24
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Journal article (peer-reviewed)abstract
- Lithium–sulfur (Li–S) battery features a high theoretical energy density, but the shuttle of soluble polysulfides between the two electrodes often results in a rapid capacity decay. Herein, a straightforward electrostatic adsorption strategy based on a cross-linked polyimidazolium separator as a snaring shield of polysulfides is reported, which suppresses the undesirable migration of polysulfides to the anode. The porous ionic network (PIN)-modified carbon nanotubes (CNTs) are successfully prepared and coated onto a commercial porous polypropylene membrane in a vacuum-filtration step. The favorable affinity of the imidazolium ring toward polysulfide via the polar interaction and the electrostatic effect of ions mitigates the undesirable shuttle of polysulfides in the electrolyte, improving the Li─S battery in terms of rate performance and cycling life. Compared to the reference PIN-free CNT-coated separator, the PIN/CNT-coated one has an increased initial capacity of 1.3 folds (up to 1394.8 mAh g−1 for PIN/CNT/PP-3) at 0.1 C.
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| 3. |
- Kang, Shuting, et al.
(author)
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ECSAS : Exploring critical scenarios from action sequence in autonomous driving
- 2023
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In: Proceeding of 2023 IEEE 32nd Asian Test Symposium (ATS). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-6
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Conference paper (peer-reviewed)abstract
- Rare critical scenarios are crucial to verify the performance of autonomous driving in different situations. Critical scenario generation requires the ability of sampling critical combinations from an infinite parameter space in the logical scenario. Existing solutions aim to explore the correlation of action parameters in the initial scenario rather than action sequences. How to model action sequences so that one can further consider the effects of different action parameters is the bottleneck of the problem. In this paper, we solve the problem by proposing the ECSAS framework. Specifically, we first propose a description language, BTScenario, allowing us to model action sequences of scenarios. We then use reinforcement learning to search for combinations of critical action parameters. Several optimizations are proposed to increase efficiency, including action mask and replay buffer. Experimental results show that our model with strong collision ability and effectively outperforms the existing methods on various nontrivial scenarios.
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| 4. |
- Su, Peng, et al.
(author)
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Enhancing Safety Assurance for Automated Driving Systems by Supporting Operation Simulation and Data Analysis
- 2023
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In: Proceeding of the 33rd European Safety and Reliability Conference. - : Research Publishing Services.
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Conference paper (peer-reviewed)abstract
- Automated Driving Systems (ADS) employ various techniques for operation perception, task planning and vehicle control. For driving on public roads, it is critical to guarantee the operational safety of such systems by attaining Minimal Risk Condition (MRC) despite unexpected environmental disruptions, human errors, functional faults and security attacks. This paper proposes a methodology to automatically identify potentially highly critical operational conditions by leveraging the design-time information in terms of vehicle architecture models and environment models. To identify the critical operating conditions, these design-time models are combined systematically with a variety of faults models for revealing the system behaviours in the presence of anomalies. The contributions of this paper are summarized as follows: 1) The design of a method for extracting related internal and external operational conditions from different system models. 2) The design of software services for identifying critical parameters and synthesizing operational data with fault injection. 3) The design for supporting operation simulation and data analysis.
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