Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks

(Unsupervised) Domain Adaptation (DA) seeks for classifying target instances when solely provided with source labeled and target unlabeled examples for training. Learning domain-invariant features helps to achieve this goal, whereas it underpins unlabeled samples drawn from a single or multiple explicit target domains (Multi-target DA). In this paper, we consider a more realistic transfer scenario: our target domain is comprised of multiple sub-targets implicitly blended with each other, so that learners could not identify which sub-target each unlabeled sample belongs to. This Blending-target Domain Adaptation (BTDA) scenario commonly appears in practice and threatens the validities of most existing DA algorithms, due to the presence of domain gaps and categorical misalignments among these hidden sub-targets. To reap the transfer performance gains in this new scenario, we propose Adversarial Meta-Adaptation Network (AMEAN). AMEAN entails two adversarial transfer learning processes. The first is a conventional adversarial transfer to bridge our source and mixed target domains. To circumvent the intra-target category misalignment, the second process presents as ``learning to adapt'': It deploys an unsupervised meta-learner receiving target data and their ongoing feature-learning feedbacks, to discover target clusters as our ``meta-sub-target'' domains. These meta-sub-targets auto-design our meta-sub-target DA loss, which empirically eliminates the implicit category mismatching in our mixed target. We evaluate AMEAN and a variety of DA algorithms in three benchmarks under the BTDA setup. Empirical results show that BTDA is a quite challenging transfer setup for most existing DA algorithms, yet AMEAN significantly outperforms these state-of-the-art baselines and effectively restrains the negative transfer effects in BTDA.Comment: CVPR-19 (oral). Code is available at http://github.com/zjy526223908/BTD

Efficacy, Safety, and Overall Quality of Life of Endoscopic Submucosal Dissection for Early Colorectal Cancer in Elderly Patients

Purpose. Studies reporting the treatment of early colorectal cancer (ECC) by endoscopic submucosal dissection (ESD) in elderly patients are lacking in China. The aim was to evaluate the efficacy, safety and overall quality of life of elderly patients with ECC who undergoing ESD. Methods. Three hundred and seventy-nine patients with 401 colorectal lesions entered into our study from March 2013 to March 2016 (Patients with an age 70 years old or older were divided into the elderly group and those who were less than 70-year-old entered the non-elderly group). Results. No significant differences were found in sex ratio, body mass index, location, endoscopic classification, pathological pattern, lesion size, mean procedure time, hospitalization days, complete excision, and en bloc resection rate between the two groups (P>0.05). No significant differences were observed between the groups in terms of complications during and after ESD procedure (P>0.05). There were no statistical differences between two groups in Quality of life index (QL-Index) and European Organization for Research and Treatment quality of life version 3.0 questionnaire (EORTC QLQ-C30) scores (P>0.05). Conclusion. ESD was relatively safe and effective for elderly patients with ECC, and it may be an recommended first-line treatment

DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object Detection

In this paper, we present a simple yet effective semi-supervised 3D object detector named DDS3D. Our main contributions have two-fold. On the one hand, different from previous works using Non-Maximal Suppression (NMS) or its variants for obtaining the sparse pseudo labels, we propose a dense pseudo-label generation strategy to get dense pseudo-labels, which can retain more potential supervision information for the student network. On the other hand, instead of traditional fixed thresholds, we propose a dynamic threshold manner to generate pseudo-labels, which can guarantee the quality and quantity of pseudo-labels during the whole training process. Benefiting from these two components, our DDS3D outperforms the state-of-the-art semi-supervised 3d object detection with mAP of 3.1% on the pedestrian and 2.1% on the cyclist under the same configuration of 1% samples. Extensive ablation studies on the KITTI dataset demonstrate the effectiveness of our DDS3D. The code and models will be made publicly available at https://github.com/hust-jy/DDS3DComment: Accepted for publication in 2023 IEEE International Conference on Robotics and Automation (ICRA

Lattice strain effects on the optical properties of MoS2 nanosheets.

"Strain engineering" in functional materials has been widely explored to tailor the physical properties of electronic materials and improve their electrical and/or optical properties. Here, we exploit both in plane and out of plane uniaxial tensile strains in MoS2 to modulate its band gap and engineer its optical properties. We utilize X-ray diffraction and cross-sectional transmission electron microscopy to quantify the strains in the as-synthesized MoS2 nanosheets and apply measured shifts of Raman-active modes to confirm lattice strain modification of both the out-of-plane and in-plane phonon vibrations of the MoS2 nanosheets. The induced band gap evolution due to in-plane and out-of-plane tensile stresses is validated by photoluminescence (PL) measurements, promising a potential route for unprecedented manipulation of the physical, electrical and optical properties of MoS2

A novel transversely isotropic strength criterion for soils based on a mobilized plane approach

The peak shear strength rules of transversely isotropic soils are stress state dependent and dependent on relative orientation between bedding plane and principal stress. Accordingly, the shear strength of transversely isotropic soils exhibits two primary characteristics: (i) the strength curve on the deviatoric plane is asymmetrical with respect to three principal stress axes; (ii) the shear strength changes with the direction angle of the bedding plane when the intermediate principal stress coefficient is a constant. In this paper, the mobilized plane is introduced and used to reveal the failure mechanism of soils. By projecting the microstructure tensor of transversely isotropic soils onto the normal of the mobilized plane, the directionality of the transversely isotropic soils is introduced into the friction rules on the mobilized plane, and a transversely isotropic strength parameter is proposed. The proposed strength parameter can extend isotropic strength criteria into transversely isotropic strength criteria. This mobilized plane approach is used to establish a novel transversely isotropic nonlinear unified strength criterion (TI-NUSC). The difficulty to establish a unified description of the asymmetrical strength curve and its evolution with direction angle is overcome by the established criterion. Comparisons between available test results and the TI-NUSC shows that the TI-NUSC can successfully describe these two primary peak strength characteristics

Fractional elastoplastic constitutive model for soils based on a novel 3D fractional plastic flow rule

A novel three-dimensional (3D) fractional plastic flow rule that is not limited by the coordinate basis of the differentiable function is proposed based on the fractional derivative and the coordinate transformation. By introducing the 3D fractional plastic flow rule into the characteristic stress space, a 3D fractional elastoplastic model for soil is established for the first time. Only five material parameters with clear physical significance are required in the proposed model. The capability of the model in capturing the strength and deformation behaviour of soils under true 3D stress conditions is verified by comparing model predictions with test results