37 research outputs found

    Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation

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    The crux of label-efficient semantic segmentation is to produce high-quality pseudo-labels to leverage a large amount of unlabeled or weakly labeled data. A common practice is to select the highly confident predictions as the pseudo-ground-truths for each pixel, but it leads to a problem that most pixels may be left unused due to their unreliability. However, we argue that every pixel matters to the model training, even those unreliable and ambiguous pixels. Intuitively, an unreliable prediction may get confused among the top classes, however, it should be confident about the pixel not belonging to the remaining classes. Hence, such a pixel can be convincingly treated as a negative key to those most unlikely categories. Therefore, we develop an effective pipeline to make sufficient use of unlabeled data. Concretely, we separate reliable and unreliable pixels via the entropy of predictions, push each unreliable pixel to a category-wise queue that consists of negative keys, and manage to train the model with all candidate pixels. Considering the training evolution, we adaptively adjust the threshold for the reliable-unreliable partition. Experimental results on various benchmarks and training settings demonstrate the superiority of our approach over the state-of-the-art alternatives

    Atomistically-informed continuum modeling and isogeometric analysis of 2D materials over holey substrates

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    This work develops, discretizes, and validates a continuum model of a molybdenum disulfide (MoS2_2) monolayer interacting with a periodic holey silicon nitride substrate via van der Waals (vdW) forces. The MoS2_2 layer is modeled as a geometrically nonlinear Kirchhoff-Love shell, and vdW forces are modeled by a Lennard-Jones potential, simplified using approximations for a smooth substrate topography. The material parameters of the shell model are calibrated by comparing small-strain tensile and bending tests with atomistic simulations. This model is efficiently discretized using isogeometric analysis (IGA) for the shell structure and a pseudo-time continuation method for energy minimization. The IGA shell model is validated against fully-atomistic calculations for several benchmark problems with different substrate geometries. The continuum simulations reproduce deflections, strains and curvatures predicted by atomistic simulations, which are known to strongly affect the electronic properties of MoS2_2, with deviations well below the modeling errors suggested by differences between the widely-used reactive empirical bond order and Stillinger-Weber interatomic potentials. Agreement with atomistic results depends on geometric nonlinearity in some cases, but a simple isotropic St. Venant-Kirchhoff model is found to be sufficient to represent material behavior. We find that the IGA discretization of the continuum model has a much lower computational cost than atomistic simulations, and expect that it will enable efficient design space exploration in strain engineering applications. This is demonstrated by studying the dependence of strain and curvature in MoS2_2 over a holey substrate as a function of the hole spacing on scales inaccessible to atomistic calculations. The results show an unexpected qualitative change in the deformation pattern below a critical hole separation

    Atomistically-informed continuum modeling and isogeometric analysis of 2D materials over holey substrates

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    This work develops, discretizes, and validates a continuum model of a molybdenum disulfide (MoS2) monolayer interacting with a periodic holey silicon nitride (Si3N4) substrate via van der Waals (vdW) forces. The MoS2 layer is modeled as a geometrically nonlinear Kirchhoff–Love shell, and vdW forces are modeled by a Lennard-Jones (LJ) potential, simplified using approximations for a smooth substrate topography. Both the shell model and LJ interactions include novel extensions informed by close comparison with fully-atomistic calculations. The material parameters of the shell model are calibrated by comparing small-strain tensile and bending tests with atomistic simulations. This model is efficiently discretized using isogeometric analysis (IGA) for the shell structure and a pseudo-time continuation method for energy minimization. The IGA shell model is validated against fully-atomistic calculations for several benchmark problems with different substrate geometries. Agreement with atomistic results depends on geometric nonlinearity in some cases, but a simple isotropic St.Venant–Kirchhoff model is found to be sufficient to represent material behavior. We find that the IGA discretization of the continuum model has a much lower computational cost than atomistic simulations, and expect that it will enable efficient design space exploration in strain engineering applications. This is demonstrated by studying the dependence of strain and curvature in MoS2 over a holey substrate as a function of the hole spacing on scales inaccessible to atomistic calculations. The results show an unexpected qualitative change in the deformation pattern below a critical hole separation

    Genome-Wide Characterization and Analysis of bHLH Transcription Factors Related to Anthocyanin Biosynthesis in Cinnamomum camphora ('Gantong 1')

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    Cinnamomum camphora is one of the most commonly used tree species in landscaping. Improving its ornamental traits, particularly bark and leaf colors, is one of the key breeding goals. The basic helix-loop-helix (bHLH) transcription factors (TFs) are crucial in controlling anthocyanin biosynthesis in many plants. However, their role in C. camphora remains largely unknown. In this study, we identified 150 bHLH TFs (CcbHLHs) using natural mutant C. camphora 'Gantong 1', which has unusual bark and leaf colors. Phylogenetic analysis revealed that 150 CcbHLHs were divided into 26 subfamilies which shared similar gene structures and conserved motifs. According to the protein homology analysis, we identified four candidate CcbHLHs that were highly conserved compared to the TT8 protein in A. thaliana. These TFs are potentially involved in anthocyanin biosynthesis in C. camphora. RNA-seq analysis revealed specific expression patterns of CcbHLHs in different tissue types. Furthermore, we verified expression patterns of seven CcbHLHs (CcbHLH001, CcbHLH015, CcbHLH017, CcbHLH022, CcbHLH101, CcbHLH118, and CcbHLH134) in various tissue types at different growth stages using qRT-PCR. This study opens a new avenue for subsequent research on anthocyanin biosynthesis regulated by CcbHLH TFs in C. camphora

    Clinical evidence of acupuncture and moxibustion for irritable bowel syndrome: A systematic review and meta-analysis of randomized controlled trials

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    BackgroundAcupuncture and moxibustion have been widely used in the treatment of Irritable Bowel Syndrome (IBS). But the evidence that acupuncture and moxibustion for IBS reduction of symptom severity and abdominal pain, and improvement of quality of life is scarce.MethodsPubMed, Embase, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journals Database (VIP), Wanfang Database, China Biomedical Literature Service System (SinoMed), and unpublished sources were searched from inception until June 30, 2022. The quality of RCTs was assessed with the Cochrane Collaboration risk of bias tool. The strength of the evidence was evaluated with the Grading of Recommendations Assessment, Development and Evaluation system (GRADE). Trial sequential analysis (TSA) was conducted to determine whether the participants in the included trials had reached optimal information size and whether the cumulative data was adequately powered to evaluate outcomes.ResultsA total of 31 RCTs were included. Acupuncture helped reduce the severity of symptoms more than pharmaceutical drugs (MD, −35.45; 95% CI, −48.21 to −22.68; I2 = 71%). TSA showed the cumulative Z score crossed O'Brien-Fleming alpha-spending significance boundaries. Acupuncture wasn't associated with symptom severity reduction (SMD, 0.03, 95% CI, −0.25 to 0.31, I2 = 46%), but exhibited therapeutic benefits on abdominal pain (SMD, −0.24; 95% CI, −0.48 to −0.01; I2 = 8%) compared to sham acupuncture. Moxibustion show therapeutic benefits compared to sham moxibustion on symptom severity (SMD, −3.46, 95% CI, −5.66 to −1.27, I2 = 95%) and abdominal pain (SMD, −2.74, 95% CI, −4.81 to −0.67, I2 = 96%). Acupuncture (SMD, −0.46; 95% CI, −0.68 to −0.24; I2 = 47%) and the combination of acupuncture and moxibustion (SMD, −2.00; 95% CI, −3.04 to −0.96; I2 = 90%) showed more benefit for abdominal pain compared to pharmacological medications as well as shams. Acupuncture (MD, 4.56; 95% CI, 1.46–7.67; I2 = 79%) and moxibustion (MD, 6.97; 95% CI, 5.78–8.16; I2 = 21%) were more likely to improve quality of life than pharmaceutical drugs.ConclusionAcupuncture and/or moxibustion are beneficial for symptom severity, abdominal pain and quality of life in IBS. However, in sham control trials, acupuncture hasn't exhibited robust and stable evidence, and moxibustion's results show great heterogeneity. Hence, more rigorous sham control trials of acupuncture or moxibustion are necessary.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=262118, identifier CRD42021262118

    Research on Energy Management Strategies of Extended-Range Electric Vehicles Based on Driving Characteristics

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    The extended-range electric vehicle (E-REV) can solve the problems of short driving range and long charging time of pure electric vehicles, but it is necessary to control the engine working points and allocate the power of the energy sources reasonably. In order to improve the fuel economy of the vehicle, an energy management strategy (EMS) that can adapt to the daily driving characteristics of the driver and adjust the control parameters online is proposed in this paper. Firstly, through principal component analysis (PCA) and iterative self-organizing data analysis techniques algorithm (ISODATA) of historical driving data, a typical driving cycle which can describe driving characteristics of the driver is constructed. Then offline optimization of control parameters by adaptive simulated annealing under each typical driving cycle and online recognition of driving cycles by extreme learning machine (ELM) are applied to the adaptive multi-workpoints energy management strategy (A-MEMS) of E-REV. In the end, compared with traditional rule-based control strategies, A-MEMS achieves good fuel-saving and emission-reduction result by simulation verification, and it explores a new and feasible solution for the continuous upgrade of the EMS
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