| 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. |
- Callaway, EM, et al.
(author)
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A multimodal cell census and atlas of the mammalian primary motor cortex
- 2021
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 598:7879, s. 86-102
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Journal article (peer-reviewed)abstract
- Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.
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| 3. |
- Li, Lianhui, et al.
(author)
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Sustainability Assessment of Intelligent Manufacturing Supported by Digital Twin
- 2020
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In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 8, s. 174988-175008
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Journal article (peer-reviewed)abstract
- As a major challenge and opportunity for traditional manufacturing, intelligent manufacturing is facing the needs of sustainable development in future. Sustainability assessment undoubtedly plays a pivotal role for future development of intelligent manufacturing. Aiming at this, the paper presents the digital twin driven information architecture of sustainability assessment oriented for dynamic evolution under the whole life cycle based on the classic digital twin mapping system. The sustainability assessment method segment of the architecture includes indicator system building, indicator value determination, indicator importance degree determination and intelligent manufacturing project assessing. A novel approach for treating the ambiguity of expert judgment in indicator value determination by introducing trapezoidal fuzzy number into analytic hierarchy process is proposed, while the complexity of the influence relationship among the indicators is processed by the integration of complex networks modeling and PROMETHEE II for the indicator importance degree determination. A two-stage evidence combination model based on evidence theory is built for intelligent manufacturing project assessing lastly. The presented digital-twin-driven information architecture and the sustainability assessment method is tested and validated on a study of sustainability assessment of 8 intelligent manufacturing projects of an air conditioning enterprise. The results of the presented method were validated by comparing them with the results of the fuzzy and rough extension of the PROMETHEE II, TOPSIS and VIKOR methods, indicator importance degree determining method by entropy and indicator value determining method by accurate expert scoring.
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| 4. |
- Nie, Duxian, et al.
(author)
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Optimizing supply chain configuration with low carbon emission
- 2020
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In: Journal of Cleaner Production. - : ELSEVIER SCI LTD. - 0959-6526 .- 1879-1786. ; 271
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Journal article (peer-reviewed)abstract
- We study a new supply chain configuration problem to optimize the amount of carbon emission in the context of a service guarantee modelling framework, called supply chain configuration problem with low carbon emission (SCCP-LCE). A novel feature of our addressed problem is the explicit consideration of carbon emission cap and trading price in the supply chain configuration setting with operating capacity. The problem is formulated as a mixed-integer nonlinear programming (MINLP) model, and optimally solved by a custom designed dynamic programming algorithm. A case study and computational experiment are performed to examine the behaviour of optimal SCCP-LCE configurations, and the effects of key input parameters: carbon emission cap, trading price, and operating capacity. Our results suggest that government-imposed carbon emission policies, in terms of emission cap and trading price, have significant impacts and interactive effects on the optimal supply chain configuration and performance, including the safety stock cost and carbon emission cost. Our model and methodology offer a new analytical framework to prescribe data-driven decision support for both firms and governmental/environmental agencies to control carbon emission, while achieving optimal business and social benefits. (C) 2020 Elsevier Ltd. All rights reserved.
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| 5. |
- Zhang, Kai, et al.
(author)
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Digital twin-based opti-state control method for a synchronized production operation system
- 2020
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In: Robotics and Computer-Integrated Manufacturing. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0736-5845 .- 1879-2537. ; 63
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Journal article (peer-reviewed)abstract
- The intelligent manufacturing strategy and customer demand have mutually promoted each other. Also, the production mode is shifting towards customized production, and more rental resources or services are introduced to the production system, therefore, the systems are becoming more complex. Compared with traditional production systems, such systems have some new features, this work calls this type of system as a synchronized production operation system (SPOS). Under such circumstances, production systems are influenced by more frequent uncertainties, and the planning-based production decision and control approach is no longer applicable. The opti-state control (OsC) method is proposed to help SPOS keep in an optimal state when uncertainties affect the system. Besides, a digital twin-based control framework (DTCF) is designed for getting the full element information needed for decision making. Based on the comprehensive information of the production system obtained by the DTCF, the OsC method is introduced to the virtual control layer to formulate the optimal target guiding the path of the system in real time through the dynamic matching mechanism (qualitative perspective). Then multi-stage synchronized control with analysis target cascading (ATC) method is used to get the local optimal state decisions (quantitative perspective). From both qualitative and quantitative aspects to ensure the system is under an optimal target path for optimal operation procedure. At last, a case study in a large-size paint making company in China is used to validate the effectiveness of the approach.
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