| 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. |
- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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| 3. |
- Liu, Quan, et al.
(författare)
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Deep reinforcement learning-based safe interaction for industrial human-robot collaboration using intrinsic reward function
- 2021
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Ingår i: Advanced Engineering Informatics. - : Elsevier BV. - 1474-0346 .- 1873-5320. ; 49
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Tidskriftsartikel (refereegranskat)abstract
- Aiming at human-robot collaboration in manufacturing, the operator's safety is the primary issue during the manufacturing operations. This paper presents a deep reinforcement learning approach to realize the real-time collision-free motion planning of an industrial robot for human-robot collaboration. Firstly, the safe human robot collaboration manufacturing problem is formulated into a Markov decision process, and the mathematical expression of the reward function design problem is given. The goal is that the robot can autonomously learn a policy to reduce the accumulated risk and assure the task completion time during human-robot collaboration. To transform our optimization object into a reward function to guide the robot to learn the expected behaviour, a reward function optimizing approach based on the deterministic policy gradient is proposed to learn a parameterized intrinsic reward function. The reward function for the agent to learn the policy is the sum of the intrinsic reward function and the extrinsic reward function. Then, a deep reinforcement learning algorithm intrinsic reward-deep deterministic policy gradient (IRDDPG), which is the combination of the DDPG algorithm and the reward function optimizing approach, is proposed to learn the expected collision avoidance policy. Finally, the proposed algorithm is tested in a simulation environment, and the results show that the industrial robot can learn the expected policy to achieve the safety assurance for industrial human-robot collaboration without missing the original target. Moreover, the reward function optimizing approach can help make up for the designed reward function and improve policy performance.
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| 4. |
- Lin, Zhenquan, et al.
(författare)
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Characterization of cross-species transcription and splicing from Penicillium to Saccharomyces cerevisiae
- 2021
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Ingår i: Journal of Industrial Microbiology and Biotechnology. - : Oxford University Press (OUP). - 1367-5435 .- 1476-5535. ; 48:9-10
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Tidskriftsartikel (refereegranskat)abstract
- Heterologous expression of eukaryotic gene clusters in yeast has been widely used for producing high-value chemicals and bioactive secondary metabolites. However, eukaryotic transcription cis-elements are still undercharacterized, and the cross-species expression mechanism remains poorly understood. Here we used the whole expression unit (including original promoter, terminator, and open reading frame with introns) of orotidine 5'-monophosphate decarboxylases from 14 Penicillium species as a showcase, and analyzed their cross-species expression in Saccharomyces cerevisiae. We found that pyrG promoters from the Penicillium species could drive URA3 expression in yeast, and that inefficient cross-species splicing of Penicillium introns might result in weak cross-species expression. Thus, this study demonstrates cross-species expression from Penicillium to yeast, and sheds light on the opportunities and challenges of cross-species expression of fungi expression units and gene clusters in yeast without refactoring for novel natural product discovery.
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| 5. |
- Liu, Zhihao, et al.
(författare)
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Adaptive real-time similar repetitive manual procedure prediction and robotic procedure generation for human-robot collaboration
- 2023
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Ingår i: Advanced Engineering Informatics. - : Elsevier BV. - 1474-0346 .- 1873-5320. ; 58
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Tidskriftsartikel (refereegranskat)abstract
- Manual procedure recognition and prediction are essential for practical human-robot collaboration in industrial tasks, such as collaborative assembly. However, current research mostly focuses on diverse human motions, while the similar repetitive manual procedures that are prevalent in real production tasks are often overlooked. Furthermore, the dynamic uncertainty caused by human-robot interferences and the generalisation of individuals, scenarios, and multiple sensor deployments pose challenges for implementing manual procedure prediction and robotic procedure generation. To address these issues, this paper proposes a real-time, similar repetitive procedure-oriented human skeleton processing system that employs the human skeleton as a robust modality. It utilises an improved deep spatial-temporal graph convolutional network and a FIFO queue-based discriminator for real-time data processing, procedure prediction, and generation. The proposed method is validated on multiple datasets with tens of individuals engaged in a real dynamic and uncertain human-robot collaborative assembly cell and able to run on entry-level hardware. The results demonstrate competitive performance of handcraft feature-free, early prediction and generalisation on individual variance, environment background, camera position, lighting conditions, and stochastic interference in human-robot collaboration.
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| 6. |
- Liu, Zhihao, et al.
(författare)
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Robot learning towards smart robotic manufacturing : A review
- 2022
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Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 77, s. 102360-
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Forskningsöversikt (refereegranskat)abstract
- Robotic equipment has been playing a central role since the proposal of smart manufacturing. Since the beginning of the first integration of industrial robots into production lines, industrial robots have enhanced productivity and relieved humans from heavy workloads significantly. Towards the next generation of manufacturing, this review first introduces the comprehensive background of smart robotic manufacturing within robotics, machine learning, and robot learning. Definitions and categories of robot learning are summarised. Concretely, imitation learning, policy gradient learning, value function learning, actor-critic learning, and model-based learning as the leading technologies in robot learning are reviewed. Training tools, benchmarks, and comparisons amongst different robot learning methods are delivered. Typical industrial applications in robotic grasping, assembly, process control, and industrial human-robot collaboration are listed and discussed. Finally, open problems and future research directions are summarised.
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| 7. |
- Liu, Zhihao, et al.
(författare)
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Task-level decision-making for dynamic and stochastic human-robot collaboration based on dual agents deep reinforcement learning
- 2021
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Ingår i: The International Journal of Advanced Manufacturing Technology. - : Springer Nature. - 0268-3768 .- 1433-3015. ; 115:11-12, s. 3533-3552
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Tidskriftsartikel (refereegranskat)abstract
- Human-robot collaboration as a multidisciplinary research topic is still pursuing the robots’ enhanced intelligence to be more human-compatible and fit the dynamic and stochastic characteristics of human. However, the uncertainties brought by the human partner challenge the task-planning and decision-making of the robot. When aiming at industrial tasks like collaborative assembly, dynamics on temporal dimension and stochasticities on the order of procedures need to be further considered. In this work, we bring a new perspective and solution based on reinforcement learning, where the problem is regarded as training an agent towards tasks in dynamic and stochastic environments. Concretely, an adapted training approach based on the deep Q learning method is proposed. This method regards both the robot and the human as the agents in the interactive training environment for deep reinforcement learning. With the consideration of task-level industrial human-robot collaboration, the training logic and the agent-environment interaction have been proposed. For the human-robot collaborative assembly tasks in the case study, it is illustrated that our method could drive the robot represented by one agent to collaborate with the human partner even the human performs randomly on the task procedures.
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| 8. |
- Yu, Senbin, et al.
(författare)
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基于旋流火焰根部熄火现象的FGM模型研究
- 2020
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Ingår i: Ranshao Kexue Yu Jishu/Journal of Combustion Science and Technology. - 1006-8740. ; 26:4, s. 301-309
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Tidskriftsartikel (refereegranskat)abstract
- A series of experimental measurements on a prototype premixed swirl burner with complex geometry were carried out using CH2O/OH-PLIF. FGM method(SFGM)taking account of strain rate was developed to study two modes of premixed swirl flame, one stabilized and the other close to blown-off flame under the same Reynolds number(Re=10000). The SFGM model in this work is related to a reaction factor, which controls the source reaction rate directly without extra dimension extension of strain rate, and thus this method could save considerable calculation time. By comparing the experimental and numerical results(OH and CH2O×OH distributions), it is clearly found that SFGM coupled with LES can capture much better results than the FGM model without considering strain rate. Specifically, the SFGM model can predict the flame structure correctly, e.g. no attached flame survives near the premixed tube exit compared with the FGM model in which the flame still survives, and the close to blow-off flame has a greater lift-off height than the stabilized flame. In addition, turbulent flame speed is proportional to turbulent fluctuation speed. The edge of main flame front is revealed to be determined jointly by the flow velocity expanding downstream and the main turbulent flame(in the CRZ)propagation velocity propagating upstream. When the equivalence ratio is decreased to the flammability limit, the reactants in the CRZ are diluted by the leaner mixtures, leading to the breaking of contact flame into smaller flame kernels. Moreover, the turbulent flame speed declines with the decreasing flame temperature while the flow speed is kept fixed, resulting in the flame front propagating downstream away from CRZ and finally blowing off.
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| 9. |
- Chen, Yu, 1990, et al.
(författare)
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Genome-scale modeling for Bacillus coagulans to understand the metabolic characteristics
- 2020
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Ingår i: Biotechnology and Bioengineering. - : Wiley. - 0006-3592 .- 1097-0290. ; 117:11, s. 3545-3558
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Tidskriftsartikel (refereegranskat)abstract
- Lactic acid is widely used in many industries, especially in the production of poly-lactic acid. Bacillus coagulans is a promising lactic acid producer in industrial fermentation due to its thermophilic property. In this study, we developed the first genome-scale metabolic model (GEM) of B. coagulans iBag597, together with an enzyme-constrained model ec-iBag597. We measured strain-specific biomass composition and integrated the data into a biomass equation. Then, we validated iBag597 against experimental data generated in this study, including amino acid requirements and carbon source utilization, showing that simulations were generally consistent with the experimental results. Subsequently, we carried out chemostats to investigate the effects of specific growth rate and culture pH on metabolism of B. coagulans. Meanwhile, we used iBag597 to estimate the intracellular metabolic fluxes for those conditions. The results showed that B. coagulans was capable of generating ATP via multiple pathways, and switched among them in response to various conditions. With ec-iBag597, we estimated the protein cost and protein efficiency for each ATP-producing pathway to investigate the switches. Our models pave the way for systems biology of B. coagulans, and our findings suggest that maintaining a proper growth rate and selecting an optimal pH are beneficial for lactate fermentation.
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| 10. |
- Deng, Huan, et al.
(författare)
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Progress of selenium deficiency in the pathogenesis of arthropathies and selenium supplement for their treatment
- 2022
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Ingår i: Biological Trace Element Research. - : Springer Nature. - 0163-4984 .- 1559-0720. ; 200, s. 4238-4249
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Forskningsöversikt (refereegranskat)abstract
- Selenium, an essential trace element for human health, exerts an indispensable effect in maintaining physiological homeostasis and functions in the body. Selenium deficiency is associated with arthropathies, such as Kashin-Beck disease, rheumatoid arthritis, osteoarthritis, and osteoporosis. Selenium deficiency mainly affects the normal physiological state of bone and cartilage through oxidative stress reaction and immune reaction. This review aims to explore the role of selenium deficiency and its mechanisms existed in the pathogenesis of arthropathies. Meanwhile, this review also summarized various experiments to highlight the crucial functions of selenium in maintaining the homeostasis of bone and cartilage.
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| 11. |
- Gao, Hongkai, et al.
(författare)
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Stepwise modeling and the importance of internal variables validation to test model realism in a data scarce glacier basin
- 2020
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Ingår i: Journal of Hydrology. - : Elsevier BV. - 0022-1694. ; 591
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Tidskriftsartikel (refereegranskat)abstract
- Model realism is of vital importance in science of hydrology, in terms of realistic representation of hydrological processes and reliability of future prediction. Here, we employed a stepwise modeling approach that leverages flexible model structures and multi-source observations for robust streamflow simulation and internal variables validation with improved model realism. This framework is demonstrated in Yigong Zangbu River (YZR) basin, a data scarce glacier basin in the upper Brahmaputra River. We designed six experiments (Exp1–6) to use modeling as a tool to understand hydrological processes in this remote cold basin with extremely high altitude. In Exp1, we started with a distributed rainfall-runoff model (FLEXD) - representing the case that snow and glacier processes were ignored. Then, we stepwisely added snow and glacier processes into FLEXD, denoted as FLEXD-S (Exp2) and FLEXD-SG (Exp3), respectively, and such improvement of model structure led to significantly improved streamflow estimates. To explore the impact of different precipitation forcing on model performance, FLEXD-SG was driven by Theissen average (Exp3) and three individual stations’ precipitation (Exp4–6). The model realism was tested by observed hydrograph, snow cover area (SCA) and glacier mass balance (GMB). Results showed that a robust and realistic hydrological modeling system was achieved in Exp6. In this modeling study, we learned that: 1) stepwise modeling is effective in investigating catchment behavior, and snow and glacier melting are the dominant hydrological processes in the YZR basin; 2) internal variables validation is beneficial to test model realism in data scarce basin; 3) the FLEXD-SG model calibrated by only one year hydrograph is sufficient to reproduce snow and glacier variations; 4) precipitation of a single station as forcing data could outperform Theissen average; 5) based on the well tested model configuration in Exp6, we analyzed simulated results, and reconstructed the long term hydrography (1961–2013), to support the potential competence for decision making on water resources management in practice. The proposed framework may significantly improve our skills in hydrological modeling over data-poor regions.
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| 12. |
- Hou, Meijun, et al.
(författare)
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Human dopaminergic system in the exercise-cognition link
- 2024
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Ingår i: Trends in Molecular Medicine. - : Elsevier. - 1471-4914 .- 1471-499X.
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Tidskriftsartikel (refereegranskat)abstract
- While the dopaminergic system is important for cognitive processes, it is also sensitive to the influence of physical activity (PA). We summarize current evidence on whether PA-related changes in the human dopaminergic system are associated with alterations in cognitive performance, discuss recent advances, and highlight challenges and opportunities for future research.
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| 13. |
- Hu, Yuan, et al.
(författare)
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GNSS-IR Model of Sea Level Height Estimation Combining Variational Mode Decomposition
- 2021
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Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - 2151-1535 .- 1939-1404. ; 14, s. 10405-10414
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Tidskriftsartikel (refereegranskat)abstract
- The Global Navigation Satellite System-Reflections (GNSS-R) signal has been confirmed to be used to retrieve sea level height. At present, the GNSS-Interferometric Reflectometry (GNSS-IR) technology based on the least square method to process signal-to-noise ratio (SNR) data is restricted by the satellite elevation angle in terms of accuracy and stability. This paper proposes a new GNSS-IR model combining variational mode decomposition (VMD) for sea level height estimation. VMD is used to decompose the SNR data into intrinsic mode functions (IMF) of layers with different frequencies, remove the IMF representing the trend item of the SNR data, and reconstruct the remaining IMF components to obtain the SNR oscillation item. In order to verify the validity of the new GNSS-IR model, the measurement data provided by the Onsala Space Observatory in Sweden is used to evaluate the performance of the algorithm and its stability in high elevation range. The experimental results show that the VMD method has good results in terms of accuracy and stability, and has advantages compared to other methods. For the half-year GNSS SNR data, the root mean square error (RMSE) and correlation coefficient of the new model based on the VMD method are 4.86 cm and 0.97, respectively.
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| 14. |
- Liu, Yi, et al.
(författare)
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Micro-hydrothermal reactions mediated grain growth during spark plasma sintering of a carbonate-containing hydroxyapatite nanopowder
- 2014
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Ingår i: Journal of the European Ceramic Society. - : Elsevier BV. - 0955-2219 .- 1873-619X. ; 34:16, s. 4395-4401
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Tidskriftsartikel (refereegranskat)abstract
- A carbonate-containing hydroxyapatite nanopowder was consolidated by spark plasma sintering at the temperatures ranging from 650 to 1100 degrees C. It was found that the water released by dehydroxylation was trapped inside the nanopores in the densified HAp bodies over 900 degrees C. Based on the analysis by the X-ray diffraction, Fourier-transform infrared spectrometry and scanning electron microscope, the water-nanopore system was evaluated and its effect on the grain growth was also investigated. It was revealed that the water existed inside the closed nanopores most probably resulted in the formation of local micro-hydrothermal environments inside bulk HAp ceramics during SPS. Therefore, the grain growth was enhanced by the local micro-hydrothermal reactions activated above 900 degrees C. In addition, abnormal grain growth was also observed when a higher temperature or higher heating rate was employed, which may be attributed to the local highly active hydrothermal reactions.
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| 15. |
- Liu, Yi, et al.
(författare)
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Reactive consolidation of layered-ternary Ti(2)AlN ceramics by spark plasma sintering of a Ti/AlN powder mixture
- 2011
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Ingår i: Journal of the European Ceramic Society. - : Elsevier BV. - 0955-2219 .- 1873-619X. ; 31:5, s. 863-868
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Tidskriftsartikel (refereegranskat)abstract
- A reactive consolidation process for preparing ternary Ti(2)AlN ceramics was investigated by spark plasma sintering (SPS). A Ti/AlN powder mixture with a molar ratio of 2:1 was consolidated at temperatures ranging from 800 to 1450 degrees C. The phase composition and microstructure evolution during the process were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) equipped with an energy dispersive spectroscopy (EDS). A series of intermediate phases, namely TiN, Ti(3)Al, Ti(3)AlN and TiAl were indentified, which revealed a reaction pathway towards the formation of Ti(2)AlN.
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| 16. |
- Wang, Tianyu, et al.
(författare)
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Data-efficient multimodal human action recognition for proactive human–robot collaborative assembly: A cross-domain few-shot learning approach
- 2024
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Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 89
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Tidskriftsartikel (refereegranskat)abstract
- With the recent vision of Industry 5.0, the cognitive capability of robots plays a crucial role in advancing proactive human–robot collaborative assembly. As a basis of the mutual empathy, the understanding of a human operator's intention has been primarily studied through the technique of human action recognition. Existing deep learning-based methods demonstrate remarkable efficacy in handling information-rich data such as physiological measurements and videos, where the latter category represents a more natural perception input. However, deploying these methods in new unseen assembly scenarios requires first collecting abundant case-specific data. This leads to significant manual effort and poor flexibility. To deal with the issue, this paper proposes a novel cross-domain few-shot learning method for data-efficient multimodal human action recognition. A hierarchical data fusion mechanism is designed to jointly leverage the skeletons, RGB images and depth maps with complementary information. Then a temporal CrossTransformer is developed to enable the action recognition with very limited amount of data. Lightweight domain adapters are integrated to further improve the generalization with fast finetuning. Extensive experiments on a real car engine assembly case show the superior performance of proposed method over state-of-the-art regarding both accuracy and finetuning efficiency. Real-time demonstrations and ablation study further indicate the potential of early recognition, which is beneficial for the robot procedures generation in practical applications. In summary, this paper contributes to the rarely explored realm of data-efficient human action recognition for proactive human–robot collaboration.
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| 17. |
- Wang, Xi Vincent, Dr. 1985-, et al.
(författare)
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A machine learning-based image processing approach for robotic assembly system
- 2021
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Ingår i: Procedia CIRP. - : Elsevier B.V.. - 2212-8271. ; , s. 906-911
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Konferensbidrag (refereegranskat)abstract
- Due to the boost of machine learning research in recent years, advanced technologies bring new possibilities to robotic assembly systems. The machine learning-based image processing methods show promising potential to tackle the challenges in the assembly process, e.g. object recognition, locating and trajectory planning. Accurate and robust methodologies are needed to guarantee the performance of the assembly tasks. In this research, a machine learning-based image processing method is proposed for the robotic assembly system. It is capable of detecting and locating assembly components based on low-cost image inputs, and manipulate the industrial robot automatically. A geometry library is also developed, which is an optional hybrid method towards accurate recognition results when needed. The proposed approach is validated and evaluated via case studies.
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| 18. |
- Yang, Liu, et al.
(författare)
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Meter-scale transparent conductive circuits based on silver nanowire networks for rigid and flexible transparent light-emitting diode screens
- 2019
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Ingår i: Optical Materials Express. - : Optical Society of America. - 2159-3930 .- 2159-3930. ; 9:12, s. 4483-4496
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Tidskriftsartikel (refereegranskat)abstract
- Meter-scale transparent conductive circuits based on silver nanowire (AgNW) networks are fabricated for transparent light-emitting diode (LED) screens on both rigid and flexible substrates. A 25-cm long AgNW transparent conductive strip is fabricated with a strip resistivity of 9.95 Omega/cm. A high uniformity is achieved in terms of film optical transmission (up to 84.5% in average) and sheet resistance (as low as 4.7 Omega/sq in average), superior to ITO. A transparent LED screen based on a 1.2-m ultralong AgNW circuit is demonstrated with LEDs emitting bright red, green and blue lights under different biases. The AgNW strip on a polyethylene terephthalate substrate shows mechanical flexibility and stable performance in bending tests. Based on this, a flexible transparent LED screen is proposed and presented. It works well when dynamically bent to a radius as small as similar to 15 mm. Therefore, the AgNW transparent conductive circuits are very promising as a replacement to ITO circuits for such smart screens, to be integrated into modern glass architectures and display videos in various public places.
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