292 research outputs found

    RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation

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    Source-Free domain adaptation transits the source-trained model towards target domain without exposing the source data, trying to dispel these concerns about data privacy and security. However, this paradigm is still at risk of data leakage due to adversarial attacks on the source model. Hence, the Black-Box setting only allows to use the outputs of source model, but still suffers from overfitting on the source domain more severely due to source model's unseen weights. In this paper, we propose a novel approach named RAIN (RegulArization on Input and Network) for Black-Box domain adaptation from both input-level and network-level regularization. For the input-level, we design a new data augmentation technique as Phase MixUp, which highlights task-relevant objects in the interpolations, thus enhancing input-level regularization and class consistency for target models. For network-level, we develop a Subnetwork Distillation mechanism to transfer knowledge from the target subnetwork to the full target network via knowledge distillation, which thus alleviates overfitting on the source domain by learning diverse target representations. Extensive experiments show that our method achieves state-of-the-art performance on several cross-domain benchmarks under both single- and multi-source black-box domain adaptation.Comment: Accepted by IJCAI 202

    Create Your World: Lifelong Text-to-Image Diffusion

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    Text-to-image generative models can produce diverse high-quality images of concepts with a text prompt, which have demonstrated excellent ability in image generation, image translation, etc. We in this work study the problem of synthesizing instantiations of a use's own concepts in a never-ending manner, i.e., create your world, where the new concepts from user are quickly learned with a few examples. To achieve this goal, we propose a Lifelong text-to-image Diffusion Model (L2DM), which intends to overcome knowledge "catastrophic forgetting" for the past encountered concepts, and semantic "catastrophic neglecting" for one or more concepts in the text prompt. In respect of knowledge "catastrophic forgetting", our L2DM framework devises a task-aware memory enhancement module and a elastic-concept distillation module, which could respectively safeguard the knowledge of both prior concepts and each past personalized concept. When generating images with a user text prompt, the solution to semantic "catastrophic neglecting" is that a concept attention artist module can alleviate the semantic neglecting from concept aspect, and an orthogonal attention module can reduce the semantic binding from attribute aspect. To the end, our model can generate more faithful image across a range of continual text prompts in terms of both qualitative and quantitative metrics, when comparing with the related state-of-the-art models. The code will be released at https://wenqiliang.github.io/.Comment: 15 pages,10 figure

    AIR-DA: Adversarial Image Reconstruction for Unsupervised Domain Adaptive Object Detection

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    Unsupervised domain adaptive object detection is a challenging vision task where object detectors are adapted from a label-rich source domain to an unlabeled target domain. Recent advances prove the efficacy of the adversarial based domain alignment where the adversarial training between the feature extractor and domain discriminator results in domain-invariance in the feature space. However, due to the domain shift, domain discrimination, especially on low-level features, is an easy task. This results in an imbalance of the adversarial training between the domain discriminator and the feature extractor. In this work, we achieve a better domain alignment by introducing an auxiliary regularization task to improve the training balance. Specifically, we propose Adversarial Image Reconstruction (AIR) as the regularizer to facilitate the adversarial training of the feature extractor. We further design a multi-level feature alignment module to enhance the adaptation performance. Our evaluations across several datasets of challenging domain shifts demonstrate that the proposed method outperforms all previous methods, of both one- and two-stage, in most settings.Comment: Accepted at IEEE Robotics and Automation Letters 202

    Flexible Energy Storage Systems Based on Electrically Conductive Hydrogels

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    The final publication is available at Elsevier via https://doi.org/10.1016/j.progpolymsci.2018.09.001 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/To power wearable electronic devices, various flexible energy storage systems have been designed to work in consecutive bending, stretching and even twisting conditions. Supercapacitors and batteries have been considered to be the most promising energy/power sources for wearable electronics; however, they need to be electrochemically sustainable and mechanically robust. Electrically conductive hydrogels (ECHs), combining the electrical properties of conductive materials with the unique features of hydrogels, are ideal frameworks to design and construct flexible supercapacitors and batteries. ECHs are intrinsically flexible to sustain large mechanical deformation; they can hold a large amount of electrolyte solution in a 3D nanostructured conducting network, providing an extremely high surface area for the required electrochemical reactions. To date, nanostructured three-dimensional ECHs have exhibited high performance when applied as active electrode materials for supercapacitors and lithium-ion batteries. Future research may attempt to develop functional ECHs with controllable size, composition, morphology, and interface. This review summarizes the material design and synthetic approach of ECHs, demonstrating the advances of percolation theory in ECH materials, and subsequently presents their effective application in flexible energy storage systems and discusses the challenges and opportunities in this field.NNSFC [grants 11472080, 51731004, 51708108]NSF of Jiangsu Province [grant BK20141336]Fundamental Research Funds for the Central UniversitiesNatural Sciences and Engineering Research Council [grant RGPIN-2014-04663

    Microwave-induced phase escape in a Josephson tunnel junction

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    This is the published version, also available here: http://dx.doi.org/10.1103/PhysRevB.77.104531.We perform both theoretical and experimental investigations on the phase escape of a current-biased Josephson tunnel junction under microwave irradiation. The switching current distributions exhibit abundant nonlinear behaviors depending on the power and frequency of the applied microwave. We present a model to describe the behavior of the primary peak in the switching current distribution, which is confirmed by our experimental results. The obtained features can be used to characterize the damping parameter of Josephson junctions

    Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese

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    Background and purpose Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population. Methods Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH)). Results In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HRSD) of PRSAS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HRSD of PRSIS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRSICH was positively associated with the risk of ICH (HRSD=1.07, 95% CI 1.01 to 1.14). PRSSAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification. Conclusions In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population

    Impacts of solid fuel use versus smoking on life expectancy at age 30 years in the rural and urban Chinese population: a prospective cohort study

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    Background: The impact of solid fuel use on life expectancy (LE) in less-developed countries remains unclear. We aimed to evaluate the potential impact of household solid fuel use on LE in the rural and urban Chinese population, with the effect of smoking as a reference. Methods: We used data from China Kadoorie Biobank (CKB) of 484,915 participants aged 30–79 free of coronary heart disease, stroke, or cancer at baseline. Analyses were performed separately for solid fuel use for cooking, solid fuel use for heating, and smoking, with participants exposed to the other two sources excluded. Solid fuels refer to coal and wood, and clean fuels refer to electricity, gas, and central heating. We used a flexible parametric Royston-Parmar model to estimate hazard ratios of all-cause mortality and predict LE at age 30. Findings: Totally, 185,077, 95,228, and 230,995 participants were included in cooking-, heating-, and smoking-related analyses, respectively. During a median follow-up of approximately 12.1 years, 12,725, 7,531, and 18,878 deaths were recorded in the respective analysis. Compared with clean fuel users who reported cooking with ventilation, participants who used solid fuels with ventilation and without ventilation had a difference in LE (95% confidence interval [CI]) at age 30 of −1.72 (−2.88, −0.57) and −2.62 (−4.16, −1.05) years for men and −1.33 (−1.85, −0.81) and −1.35 (−2.02, −0.67) years for women, respectively. The difference in LE (95% CI) for heating was −2.23 (−3.51, −0.95) years for men and −1.28 (−2.08, −0.48) years for women. In rural men, the LE reduction (95% CI) related to solid fuel use for cooking (−2.55; −4.51, −0.58) or heating (−3.26; −6.09, 0.44) was more than that related to smoking (−1.71; −2.54, −0.89). Conversely, in urban men, the LE reduction (95% CI) related to smoking (−3.06; −3.56, −2.56) was more than that related to solid fuel use for cooking (−1.28; −2.61, 0.05) and heating (−1.90; −3.16, −0.65). Similar results were observed in women but with a smaller magnitude. Interpretation: In this Chinese population, the harm to LE from household use of solid fuels was greater than that from smoking in rural residents. Conversely, the negative impact of smoking was greater than solid fuel use in urban residents. Our findings highlight the complexity and diversity of the factors affecting LE in less-developed populations

    Fretting wear behavior of graphite-like carbon films with bias-graded deposition

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    Although graphite-like carbon (GLC) films have been used to protect the engineering components due to their high mechanical properties and low friction coefficients, the poor interfacial bonding strength and high internal stress can lead their rapid failure. In this study, the bias-gradient (30–120 V) as well as the usual constant bias protocols (30, 60 and 120 V) has been adopted to deposit the GLC films on 316 L stainless steel and silicon using unbalanced magnetron sputtering technology. Based upon the microstructure and composition analysis by SEM, AFM, XRD, Raman and XPS, the sp3 content and compactness of the films are increased with the increase of the deposition bias. Compared to the film at the constant bias of 120 V, the bias-graded film has a comparable hardness but superior adhesive strength. Detailed fretting wear testing under ambient air and dry N2 atmospheres against 25 mm diameter Si3N4 ball has been carried out. The friction curves disclosed a three-stage evolution feature: the surface working area, the interlayer transition area and the coating failure area. The bias-graded film displayed the lowest friction coefficient and the longest fatigue life. Further the fretting mechanisms at different stages have been elaborated in terms of the chemical composition, microstructure and mechanical properties
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