Vision Learners Meet Web Image-Text Pairs

Most recent self-supervised learning methods are pre-trained on the well-curated ImageNet-1K dataset. In this work, given the excellent scalability of web data, we consider self-supervised pre-training on noisy web sourced image-text paired data. First, we conduct a benchmark study of representative self-supervised pre-training methods on large-scale web data in a like-for-like setting. We compare a range of methods, including single-modal ones that use masked training objectives and multi-modal ones that use image-text constrastive training. We observe that existing multi-modal methods do not outperform their single-modal counterparts on vision transfer learning tasks. We derive an information-theoretical view to explain these benchmark results, which provides insight into how to design a novel vision learner. Inspired by this insight, we present a new visual representation pre-training method, MUlti-modal Generator~(MUG), that learns from scalable web sourced image-text data. MUG achieves state-of-the-art transfer performance on a variety of tasks and demonstrates promising scaling properties. Pre-trained models and code will be made public upon acceptance.Comment: Project page: https://bzhao.me/MUG

Facile Synthesis of a 3,4-Ethylene-Dioxythiophene (EDOT) Derivative for Ease of Bio-Functionalization of the Conducting Polymer PEDOT

In the pursuit of conducting polymer based bio-functional devices, a cost-effective and high yield synthesis method for a versatile monomer is desired. We report here a new synthesis strategy for a versatile monomer 2-methylene-2,3-dihydrothieno (3,4-b) (1,4) dioxine, or 3,4-ethylenedioxythiophene with a exomethylene side group (EDOT-EM). Compared to the previously reported synthesis route, the new strategy uses less steps, with faster reaction rate, and higher yield. The presence of EM group opens up endless possibility for derivatization via either hydro-alkoxy addition or thiol-ene click chemistry. EDOT-EM could be polymerized into stable and low impedance PEDOT-EM polymer using electro-polymerization method on different conducting substrates at both macro and micro scales. Facile post-functionalization of PEDOT-EM with molecules of varying size and functionality (from small molecules to DNAs and proteins) was achieved. The new synthetic route of EDOT-EM and the ease of post-functionalization of PEDOT-EM will greatly accelerate the use of conducting polymer in a broad range of organic electronics and bioelectronics applications

Facile Synthesis of a 3,4-Ethylene-Dioxythiophene (EDOT) Derivative for Ease of Bio-Functionalization of the Conducting Polymer PEDOT

In the pursuit of conducting polymer based bio-functional devices, a cost-effective and high yield synthesis method for a versatile monomer is desired. We report here a new synthesis strategy for a versatile monomer 2-methylene-2,3-dihydrothieno (3,4-b) (1,4) dioxine, or 3,4-ethylenedioxythiophene with a exomethylene side group (EDOT-EM). Compared to the previously reported synthesis route, the new strategy uses less steps, with faster reaction rate, and higher yield. The presence of EM group opens up endless possibility for derivatization via either hydro-alkoxy addition or thiol-ene click chemistry. EDOT-EM could be polymerized into stable and low impedance PEDOT-EM polymer using electro-polymerization method on different conducting substrates at both macro and micro scales. Facile post-functionalization of PEDOT-EM with molecules of varying size and functionality (from small molecules to DNAs and proteins) was achieved. The new synthetic route of EDOT-EM and the ease of post-functionalization of PEDOT-EM will greatly accelerate the use of conducting polymer in a broad range of organic electronics and bioelectronics applications

SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation

High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. Firstly, these algorithms tend to focus on local information, neglecting non-local information between different pixel patches. Secondly, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Thirdly, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a Superpixel High-Resolution SAR Imaging Network (SPHR-SAR-Net) for rapid despeckling in high-resolution SAR mode. Based on the concept of superpixel techniques, we initially combine non-convex and non-local total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the Alternating Direction Method of Multipliers (ADMM) algorithm and unfold it into a Deep Unfolded Network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the Deep Unfolded Network is compatible with high-resolution imaging modes such as spotlight, staring spotlight, and sliding spotlight. In this paper, we demonstrate the superiority of SPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that SPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results

A van der Waals pn heterojunction with organic/inorganic semiconductors

van der Waals (vdW) heterojunctions formed by two-dimensional (2D) materials have attracted tremendous attention due to their excellent electrical/optical properties and device applications. However, current 2D heterojunctions are largely limited to atomic crystals, and hybrid organic/inorganic structures are rarely explored. Here, we fabricate hybrid 2D heterostructures with p-type dioctylbenzothienobenzothiophene (C8-BTBT) and n-type MoS2. We find that few-layer C8-BTBT molecular crystals can be grown on monolayer MoS2 by vdW epitaxy, with pristine interface and controllable thickness down to monolayer. The operation of the C8-BTBT/MoS2 vertical heterojunction devices is highly tunable by bias and gate voltages between three different regimes: interfacial recombination, tunneling and blocking. The pn junction shows diode-like behavior with rectifying ratio up to 105 at the room temperature. Our devices also exhibit photovoltaic responses with power conversion efficiency of 0.31% and photoresponsivity of 22mA/W. With wide material combinations, such hybrid 2D structures will offer possibilities for opto-electronic devices that are not possible from individual constituents.Comment: 16 pages, 4 figure

Optimal configuration of energy storage considering flexibility requirements and operational risks in a power system

The integration of renewable energy units into power systems brings a huge challenge to the flexible regulation ability. As an efficient and convenient flexible resource, energy storage systems (ESSs) have the advantages of fast-response characteristics and bi-directional power conversion, which can provide flexible support for the power system. This paper establishes an optimization model for the ESS based on a bi-level programming model. The upper-level model optimizes the decision strategy of ESS configuration planning. The lower-level model is based on scenario analysis theory to simulate the operation of typical daily scenarios. Flexibility requirement constraints are added to characterize the required flexibility resources of the power system. In addition, the conditional value-at-risk (CVaR) is applied to characterize the risk of wind curtailment and load shedding during operation. To simplify the model, a set of association constraints is introduced to convert the original bi-level programming model into a direct-solvable single-level mixed-integer linear programming (MILP) model. Finally, the effectiveness of the proposed model is verified through case studies