The consistency of estimator under fixed design regression model with NQD errors

In this article, basing on NQD samples, we investigate the fixed design nonparametric regression model, where the errors are pairwise NQD random errors, with fixed design points, and an unknown function. Nonparametric weighted estimator will be introduced and its consistency is studied. As special case, the consistency result for weighted kernel estimators of the model is obtained. This extends the earlier work on independent random and dependent random errors to NQD case

Learning based Deep Disentangling Light Field Reconstruction and Disparity Estimation Application

Light field cameras have a wide range of uses due to their ability to simultaneously record light intensity and direction. The angular resolution of light fields is important for downstream tasks such as depth estimation, yet is often difficult to improve due to hardware limitations. Conventional methods tend to perform poorly against the challenge of large disparity in sparse light fields, while general CNNs have difficulty extracting spatial and angular features coupled together in 4D light fields. The light field disentangling mechanism transforms the 4D light field into 2D image format, which is more favorable for CNN for feature extraction. In this paper, we propose a Deep Disentangling Mechanism, which inherits the principle of the light field disentangling mechanism and further develops the design of the feature extractor and adds advanced network structure. We design a light-field reconstruction network (i.e., DDASR) on the basis of the Deep Disentangling Mechanism, and achieve SOTA performance in the experiments. In addition, we design a Block Traversal Angular Super-Resolution Strategy for the practical application of depth estimation enhancement where the input views is often higher than 2x2 in the experiments resulting in a high memory usage, which can reduce the memory usage while having a better reconstruction performance

Proximity induced pseudogap in mesoscopic superconductor/normal-metal bilayers

Recent scanning tunneling microscopy measurements of the proximity effect in Au/La$_{2-x}$Sr$_{x}$CuO$_{4}$ and La$_{1.55}$Sr$_{0.45}$CuO$_{4}$/La$_{2-x}$Sr$_{x}$CuO$_{4}$ bilayers showed a proximity-induced pseudogap [Yuli et al., Phys. Rev. Lett. {\bf 103}, 197003 (2009)]. We describe the proximity effect in mesoscopic superconductor/normal-metal bilayers by using the Bogoliubov-de Gennes equations for a tight-binding Hamiltonian with competing antiferromagnetic and d-wave superconductivity orders . The temperature dependent local density of states is calculated as a function of the distance from the interface. Bound state due to both d-wave and spin density wave gaps are formed in the normal metal for energies less than the respective gaps. If there is a mismatch between the Fermi velocities in the two layers we observe that these states will shift in energy when spin density wave order is present, thus inducing a minigap at finite energy. We conclude that the STM measurement in the proximity structures is able to distinguish between the two scenarios proposed for the pseudogap (competing or precursor to superconductivity)

Improving Visual Quality and Transferability of Adversarial Attacks on Face Recognition Simultaneously with Adversarial Restoration

Adversarial face examples possess two critical properties: Visual Quality and Transferability. However, existing approaches rarely address these properties simultaneously, leading to subpar results. To address this issue, we propose a novel adversarial attack technique known as Adversarial Restoration (AdvRestore), which enhances both visual quality and transferability of adversarial face examples by leveraging a face restoration prior. In our approach, we initially train a Restoration Latent Diffusion Model (RLDM) designed for face restoration. Subsequently, we employ the inference process of RLDM to generate adversarial face examples. The adversarial perturbations are applied to the intermediate features of RLDM. Additionally, by treating RLDM face restoration as a sibling task, the transferability of the generated adversarial face examples is further improved. Our experimental results validate the effectiveness of the proposed attack method.Comment: \copyright 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

B-vitamin consumption and the prevalence of diabetes and obesity among the US adults: population based ecological study

<p>Abstract</p> <p>Background</p> <p>The global increased prevalence of obesity and diabetes occurred after the worldwide spread of B-vitamins fortification, in which whether long-term exposure to high level of B vitamins plays a role is unknown. Our aim was to examine the relationships between B-vitamins consumption and the obesity and diabetes prevalence.</p> <p>Methods</p> <p>This population based ecological study was conducted to examine possible associations between the consumption of the B vitamins and macronutrients and the obesity and diabetes prevalence in the US population using the per capita consumption data from the US Economic Research Service and the prevalence data from the US Centers for Disease Control and Prevention.</p> <p>Results</p> <p>The prevalences of diabetes and adult obesity were highly correlated with per capita consumption of niacin, thiamin and riboflavin with a 26-and 10-year lag, respectively (<it>R</it>²= 0.952, 0.917 and 0.83 for diabetes, respectively, and <it>R</it>²= 0.964, 0.975 and 0.935 for obesity, respectively). The diabetes prevalence increased with the obesity prevalence with a 16-year lag (<it>R</it>²= 0.975). The relationships between the diabetes or obesity prevalence and per capita niacin consumption were similar both in different age groups and in male and female populations. The prevalence of adult obesity and diabetes was highly correlated with the grain contribution to niacin (<it>R</it>²= 0.925 and 0.901, respectively), with a 10-and 26-year lag, respectively. The prevalence of obesity in US adults during 1971-2004 increased in parallel with the increase in carbohydrate consumption with a 10-year lag. The per capita energy and protein consumptions positively correlated with the obesity prevalence with a one-year lag. Moreover, there was an 11-year lag relationship between per capita energy and protein consumption and the consumption of niacin, thiamin and riboflavin (<it>R</it>²= 0.932, 0.923 and 0.849 for energy, respectively, and <it>R</it>²= 0.922, 0.878 and 0.787 for protein, respectively).</p> <p>Conclusions</p> <p>Long-term exposure to high level of the B vitamins may be involved in the increased prevalence of obesity and diabetes in the US in the past 50 years. The possible roles of B-vitamins fortification and excess niacin consumption in the increased prevalence of obesity and diabetes were discussed.</p

Photo-induced Charge Transfer in Azapyrene-Tetrathiafulvalene Triads

Tetrathiafulvalene (TTF)-based donor-acceptor (D–A) ensembles have attracted a lot of attention due to their unique (opto)electronic properties and potential applications in organic semiconductors, photovoltaics, sensors, switches and molecular electronics.1-3 To develop high-performance electronic devices, control over multiple charge-transfer (CT) pathways in D-A ensembles is of prime importance. Recently, we have demonstrated chemical and ultrafast optical regulation of distinct photo-induced charge flows within such D-A systems.4,5 As a continuation of our ongoing work, we herein describe redox and optical properties of new D–A ensembles (Chart 1) which were prepared by covalent linkage of two TTF donor units to a central azapyrene acceptor either with or without two tert-butyl groups. A detailed experimental and theoretical study of electronic interactions between D and A units and ICT processes in these triads is presented

Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow

A major challenge for video semantic segmentation is the lack of labeled data. In most benchmark datasets, only one frame of a video clip is annotated, which makes most supervised methods fail to utilize information from the rest of the frames. To exploit the spatio-temporal information in videos, many previous works use pre-computed optical flows, which encode the temporal consistency to improve the video segmentation. However, the video segmentation and optical flow estimation are still considered as two separate tasks. In this paper, we propose a novel framework for joint video semantic segmentation and optical flow estimation. Semantic segmentation brings semantic information to handle occlusion for more robust optical flow estimation, while the non-occluded optical flow provides accurate pixel-level temporal correspondences to guarantee the temporal consistency of the segmentation. Moreover, our framework is able to utilize both labeled and unlabeled frames in the video through joint training, while no additional calculation is required in inference. Extensive experiments show that the proposed model makes the video semantic segmentation and optical flow estimation benefit from each other and outperforms existing methods under the same settings in both tasks.Comment: Published in AAAI 202