| 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. |
- Sun, Jiaying, et al.
(författare)
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SreC-dependent adaption to host iron environments regulates the transition of trophic stages and developmental processes of Curvularia lunata
- 2024
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Ingår i: Molecular Plant Pathology. - 1464-6722. ; 25:3
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Tidskriftsartikel (refereegranskat)abstract
- Plant pathogens are challenged by host-derived iron starvation or excess during infection, but the mechanism of plant pathogens rapidly adapting to the dynamic host iron environments to assimilate iron for invasion and colonization remains largely unexplored. Here, we found that the GATA transcription factor SreC in Curvularia lunata is required for virulence and adaption to the host iron excess environment. SreC directly binds to the ATGWGATAW element in an iron-dependent manner to regulate the switch between different iron assimilation pathways, conferring adaption to host iron environments in different trophic stages of C. lunata. SreC also regulates the transition of trophic stages and developmental processes in C. lunata. SreC-dependent adaption to host iron environments is essential to the infectious growth and survival of C. lunata. We also demonstrate that CgSreA (a SreC orthologue) plays a similar role in Colletotrichum graminicola. We conclude that Sre mediates adaption to the host iron environment during infection, and the function is conserved in hemibiotrophic fungi.
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| 3. |
- Sun, Mingyue, et al.
(författare)
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Out-of-order execution enabled deep reinforcement learning for dynamic additive manufacturing scheduling
- 2025
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Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 91
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Tidskriftsartikel (refereegranskat)abstract
- Additive Manufacturing (AM) has revolutionized the production landscape by enabling on-demand customized manufacturing. However, the efficient management of dynamic AM orders poses significant challenges for production planning and scheduling. This paper addresses the dynamic scheduling problem considering batch processing, random order arrival and machine eligibility constraints, aiming to minimize total tardiness in a parallel non-identical AM machine environment. To tackle this problem, we propose the out-of-order enabled dueling deep Q network (O3-DDQN) approach. In the proposed approach, the problem is formulated as a Markov decision process (MDP). Three-dimensional features, encompassing dynamic orders, AM machines, and delays, are extracted using a ‘look around’ method to represent the production status at a rescheduling point. Additionally, five novel composite scheduling rules based on the out-of-order principle are introduced for selection when an AM machine completes processing or a new order arrives. Moreover, we design a reward function that is strongly correlated with the objective to evaluate the agent's chosen action. Experimental results demonstrate the superiority of the O3-DDQN approach over single scheduling rules, randomly selected rules, and the classic DQN method. The average improvement rate of performance reaches 13.09% compared to composite scheduling rules and random rules. Additionally, the O3-DDQN outperforms the classic DQN agent with a 6.54% improvement rate. The O3-DDQN algorithm improves scheduling in dynamic AM environments, enhancing productivity and on-time delivery. This research contributes to advancing AM production and offers insights into efficient resource allocation.
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| 4. |
- Zhao, Mingyue, et al.
(författare)
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Advances in Two-Dimensional Materials for Optoelectronics Applications
- 2022
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Ingår i: Crystals. - : MDPI. - 2073-4352. ; 12:8
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Forskningsöversikt (refereegranskat)abstract
- The past one and a half decades have witnessed the tremendous progress of two-dimensional (2D) crystals, including graphene, transition-metal dichalcogenides, black phosphorus, MXenes, hexagonal boron nitride, etc., in a variety of fields. The key to their success is their unique structural, electrical, mechanical and optical properties. Herein, this paper gives a comprehensive summary on the recent advances in 2D materials for optoelectronic approaches with the emphasis on the morphology and structure, optical properties, synthesis methods, as well as detailed optoelectronic applications. Additionally, the challenges and perspectives in the current development of 2D materials are also summarized and indicated. Therefore, this review can provide a reference for further explorations and innovations of 2D material-based optoelectronics devices.
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