189 research outputs found

    Relabeling Minimal Training Subset to Flip a Prediction

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    When facing an unsatisfactory prediction from a machine learning model, it is crucial to investigate the underlying reasons and explore the potential for reversing the outcome. We ask: can we result in the flipping of a test prediction xtx_t by relabeling the smallest subset St\mathcal{S}_t of the training data before the model is trained? We propose an efficient procedure to identify and relabel such a subset via an extended influence function. We find that relabeling fewer than 1% of the training points can often flip the model's prediction. This mechanism can serve multiple purposes: (1) providing an approach to challenge a model prediction by recovering influential training subsets; (2) evaluating model robustness with the cardinality of the subset (i.e., St|\mathcal{S}_t|); we show that St|\mathcal{S}_t| is highly related to the noise ratio in the training set and St|\mathcal{S}_t| is correlated with but complementary to predicted probabilities; (3) revealing training points lead to group attribution bias. To the best of our knowledge, we are the first to investigate identifying and relabeling the minimal training subset required to flip a given prediction.Comment: Under revie

    Mildly Constrained Evaluation Policy for Offline Reinforcement Learning

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    Offline reinforcement learning (RL) methodologies enforce constraints on the policy to adhere closely to the behavior policy, thereby stabilizing value learning and mitigating the selection of out-of-distribution (OOD) actions during test time. Conventional approaches apply identical constraints for both value learning and test time inference. However, our findings indicate that the constraints suitable for value estimation may in fact be excessively restrictive for action selection during test time. To address this issue, we propose a Mildly Constrained Evaluation Policy (MCEP) for test time inference with a more constrained target policy for value estimation. Since the target policy has been adopted in various prior approaches, MCEP can be seamlessly integrated with them as a plug-in. We instantiate MCEP based on TD3-BC [Fujimoto and Gu, 2021] and AWAC [Nair et al., 2020] algorithms. The empirical results on MuJoCo locomotion tasks show that the MCEP significantly outperforms the target policy and achieves competitive results to state-of-the-art offline RL methods. The codes are open-sourced at https://github.com/egg-west/MCEP.git

    Hydrodynamics and heat transfer of suspended surface in a supercritical cfb furnace

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    With the scaling-up of CFB boilers, more heating surfaces like suspended surfaces and/or mid-partition walls, are arranged in the furnace to ensure adequate heat absorption. The length of suspended surface reaches almost half height of the furnace in the Baima 600MW supercritical CFB boiler. Since the gas-solids hydrodynamics and heat transfer on those surfaces are different from that on waterwall, further researches are needed to investigate the characteristics of hydrodynamics and heat transfer on the suspended surfaces. Beside the experimental measurements on the suspended surfaces in a scale down test rig, the hydrodynamic characteristics on the suspended surfaces were computed by a CFD simulation combined with EMMS model in a supercritical CFB of annular furnace. The results present an uneven axial solid concentration profile on the suspended surface, and descending particles are found on some locations especially where those surfaces far away from the furnace exits. Based on the gas-solids hydrodynamic results, the modified cluster renewal model was applied in the heat transfer coefficient calculation of the suspended surfaces. The result shows the heat transfer coefficient varies with the height and it has difference between two sides of a surface. In addition, the average heat transfer coefficients of suspended surface at different locations are compared. References Basu P, Nag P K. Heat transfer to walls of a circulating fluidized-bed furnace[J]. Chemical Engineering Science, 1996, 51(1): 1-26. Cen K F, Ni M J, Luo Z Y, et al. Theoretical design and operation of circulating fluidized bed boiler[J]. China Electric Power Press, Beijing, 1998: 647-663. Cheng L M, Wang Q H, Shi Z L, et al. Heat transfer in a large circulating fluidized bed boiler[J]. Journal of Power Engineering, 2006, 26(3): 305-310. Huang C, Cheng L M, Zhou X L, et al. Suspended surface heat transfer in a large circulating fluidized bed boiler furnace[J]. Journal of Zhejiang University. Engineering Science, 2012, 46(11): 2128-2132. Sundaresan R, Kolar A K. Axial heat transfer correlations in a circulating fluidized bed riser[J]. Applied Thermal Engineering, 2012. * “Strategic Priority Research Program” of the Chinese Academy of Sciences, Grant No. XDA0703010

    Isolation, purification and PEG-mediated transient expression of mesophyll protoplasts in Camellia oleifera

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    Background: Camellia oleifera (C. oleifera) is a woody edible oil crop of great economic importance. Because of the lack of modern biotechnology research, C. oleifera faces huge challenges in both breeding and basic research. The protoplast and transient transformation system plays an important role in biological breeding, plant regeneration and somatic cell fusion. The objective of this present study was to develop a highly efficient protocol for isolating and purifying mesophyll protoplasts and transient transformation of C. oleifera. Several critical factors for mesophyll protoplast isolation from C. oleifera, including starting material (leaf age), pretreatment, enzymatic treatment (type of enzyme, concentration and digestion time), osmotic pressure and purification were optimized. Then the factors affecting the transient transformation rate of mesophyll protoplasts such as PEG molecular weights, PEG4000 concentration, plasmid concentration and incubation time were explored.Results: The in vitro grown seedlings of C. oleifera 'Huashuo' were treated in the dark for 24 h, then the 1st to 2nd true leaves were picked and vacuumed at - 0.07 MPa for 20 min. The maximum yield (3.5 x 10(7)/g.W) and viability (90.9%) of protoplast were reached when the 1st to 2nd true leaves were digested in the enzymatic solution containing1.5% (w/v) Cellulase R-10, 0.5% (w/v) Macerozyme R-10 and 0.25% (w/v) Snailase and 0.4 M mannitol for 10 h. Moreover, the protoplast isolation method was also applicable to the other two cultivars, the protoplast yield for 'TXP14' and 'DP47' was 1.1 x 10(7)/g.FW and 2.6 x 10(7)/g. FW, the protoplast viability for 'TXP14' and 'DP47' was 90.0% and 88.2%. The purification effect was the best when using W buffer as a cleaning agent by centrifugal precipitation. The maximum transfection efficiency (70.6%) was obtained with the incubation of the protoplasts with 15 mu g plasmid and 40% PEG4000 for 20 min.Conclusion: In summary, a simple and efficient system for isolation and transient transformation of C. oleifera mesophyll protoplast is proposed, which is of great significance in various aspects of C. oleifera research, including the study of somatic cell fusion, genome editing, protein function, signal transduction, transcriptional regulation and multi-omics analyses
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