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- 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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| 3. |
- Kristan, Matej, et al.
(author)
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The Ninth Visual Object Tracking VOT2021 Challenge Results
- 2021
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In: 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021). - : IEEE COMPUTER SOC. - 9781665401913 ; , s. 2711-2738
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website(1).
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| 5. |
- Bhat, Goutam, et al.
(author)
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NTIRE 2022 Burst Super-Resolution Challenge
- 2022
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In: 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2022). - : IEEE. - 9781665487399 - 9781665487405 ; , s. 1040-1060
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Conference paper (peer-reviewed)abstract
- Burst super-resolution has received increased attention in recent years due to its applications in mobile photography. By merging information from multiple shifted images of a scene, burst super-resolution aims to recover details which otherwise cannot be obtained using a simple input image. This paper reviews the NTIRE 2022 challenge on burst super-resolution. In the challenge, the participants were tasked with generating a clean RGB image with 4x higher resolution, given a RAW noisy burst as input. That is, the methods need to perform joint denoising, demosaicking, and super-resolution. The challenge consisted of 2 tracks. Track 1 employed synthetic data, where pixel-accurate high-resolution ground truths are available. Track 2 on the other hand used real-world bursts captured from a handheld camera, along with approximately aligned reference images captured using a DSLR. 14 teams participated in the final testing phase. The top performing methods establish a new state-of-the-art on the burst super-resolution task.
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| 7. |
- Du, Jiawei, et al.
(author)
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Proteomic profiling of muscular adaptations to short-term concentric versus eccentric exercise training in humans
- 2024
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In: Molecular & Cellular Proteomics. - : Elsevier. - 1535-9476 .- 1535-9484. ; 23:4
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Journal article (peer-reviewed)abstract
- The molecular mechanisms underlying muscular adaptations to concentric (CON) and eccentric (ECC) exercise training have been extensively explored. However, most previous studies have focused on specifically selected proteins, thus, unable to provide a comprehensive protein profile and potentially missing the crucial mechanisms underlying muscular adaptation to exercise training. We herein aimed to investigate proteomic profiles of human skeletal muscle in response to short-term resistance training. Twenty young males were randomly and evenly assigned to two groups to complete a 4-week either ECC or CON training program. Measurements of body composition and physiological function of the quadriceps femoris were conducted both before and after the training. Muscle biopsies from the vastus lateralis of randomly selected participants (five in ECC and four in CON) of both before and after the training were analyzed using the liquid-chromatography tandem mass spectrometry in combination with bioinformatics analysis. Neither group presented a significant difference in body composition or leg muscle mass; however, muscle peak torque, total work, and maximal voluntary contraction were significantly increased after the training in both groups. Proteomics analysis revealed 122 differentially abundant proteins (DAPs; p value < 0.05 & fold change >1.5 or <0.67) in ECC, of which the increased DAPs were mainly related to skeletal muscle contraction and cytoskeleton and enriched specifically in the pentose phosphate pathway, extracellular matrix-receptor interaction, and PI3K-Akt signaling pathway, whereas the decreased DAPs were associated with the mitochondrial respiratory chain. One hundred one DAPs were identified in CON, of which the increased DAPs were primarily involved in translation/ protein synthesis and the mitochondria respiratory, whereas the decreased DAPs were related to metabolic processes, cytoskeleton, and de-ubiquitination. In conclusion, the 4-week CON and ECC training resulted in distinctly different proteomic profiles, especially in proteins related to muscular structure and metabolism.
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| 9. |
- Ge, L., et al.
(author)
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Data Augmentation Method for Transformer Fault Based on Improved Auto-Encoder Under the Condition of Insufficient Data
- 2021
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In: Diangong Jishu Xuebao/Transactions of China Electrotechnical Society. - : China Machine Press. - 1000-6753. ; 36, s. 84-94
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Journal article (peer-reviewed)abstract
- There are few transformer faults, which makes the methods of transformer fault diagnosis based on machine learning lack of data. For this reason, a method based on improved auto-encoder (IAE) is proposed to augment transformer fault data. Firstly, to solve the problem of limited data and lack of diversity in the traditional automatic encoder, an improved strategy for generating samples for transformer faults is proposed. Secondly, considering that the traditional convolutional neural network will lose a lot of feature information in the pooling operation, the improved convolutional neural network (ICNN) is constructed as the classifier of fault diagnosis. Finally, the effectiveness and adaptability of the proposed method are verified by the actual data. The simulation results show that IAE can take into account the distribution and diversity of data at the same time, and the generated transformer fault data can improve the performance of the classifier better than the traditional augmentation methods such random over-sampling method, synthetic minority over-sampling technique, and auto-encoder. Compared with traditional classifiers, ICNN has higher fault diagnosis accuracy before and after data augmentation.
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| 10. |
- Ge, Quanbo, et al.
(author)
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A Novel Adaptive Kalman Filter Based on Credibility Measure
- 2023
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In: IEEE-CAA JOURNAL OF AUTOMATICA SINICA. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-9266. ; 10:1, s. 103-120
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Journal article (peer-reviewed)abstract
- It is quite often that the theoretic model used in the Kalman filtering may not be sufficiently accurate for practical applications, due to the fact that the covariances of noises are not exactly known. Our previous work reveals that in such scenario the filter calculated mean square errors (FMSE) and the true mean square errors (TMSE) become inconsistent, while FMSE and TMSE are consistent in the Kalman filter with accurate models. This can lead to low credibility of state estimation regardless of using Kalman filters or adaptive Kalman filters. Obviously, it is important to study the inconsistency issue since it is vital to understand the quantitative influence induced by the inaccurate models. Aiming at this, the concept of credibility is adopted to discuss the inconsistency problem in this paper. In order to formulate the degree of the credibility, a trust factor is constructed based on the FMSE and the TMSE. However, the trust factor can not be directly computed since the TMSE cannot be found for practical applications. Based on the definition of trust factor, the estimation of the trust factor is successfully modifled to online estimation of the TMSE. More importantly, a necessary and sufficient condition is found, which turns out to be the basis for better design of Kalman filters with high performance. Accordingly, beyond trust factor estimation with Sage-Husa technique (TFE-SHT), three novel trust factor estimation methods, which are directly numerical solving method (TFE-DNS), the particle swarm optimization method (PSO) and expectation max-imization-particle swarm optimization method (EM-PSO) are proposed. The analysis and simulation results both show that the proposed TFE-DNS is better than the TFE-SHT for the case of single unknown noise covariance. Meanwhile, the proposed EM-PSO performs completely better than the EM and PSO on the estimation of the credibility degree and state when both noise covariances should be estimated online.
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